Tag deep-learning 一大堆深度学习论文_tag deep learning

作者：2023面试高手 | 2024-05-13 20:30:55

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tag deep learning

Tag deep-learning [159 articles]

Recent papers classified by the tag deep-learning.

	✔ Deep Learning without Poor Local Minima (23 May 2016) by Kenji Kawaguchi posted to deep-learning learning-theory machine-learning by memming on 2016-05-24 21:56:26 along with 1 person Abstract
	✔ Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records Scientific Reports, Vol. 6 (17 May 2016), 26094, doi:10.1038/srep26094 by Riccardo Miotto, Li Li, Brian A. Kidd, Joel T. Dudley posted to deep-learning by hans_meine on 2016-05-23 10:04:13
	✔ Deep learning Nature, Vol. 521, No. 7553. (28 May 2015), pp. 436-444, doi:10.1038/nature14539 by Yann LeCun, Yoshua Bengio, Geoffrey Hinton posted to deep-learning neural-networks by vankov on 2016-05-22 21:20:13 along with 27 people
	✔ Where Do Features Come From? Cogn Sci, Vol. 38, No. 6. (1 August 2014), pp. 1078-1101, doi:10.1111/cogs.12049 by Geoffrey Hinton posted to deep-learning neural-networks by vankov on 2016-05-22 21:12:41 along with 1 group Abstract
	✔ Modeling language and cognition with deep unsupervised learning: a tutorial overview. Frontiers in psychology, Vol. 4 (2013), doi:10.3389/fpsyg.2013.00515 by Marco Zorzi, Alberto Testolin, Ivilin P. Stoianov posted to bayesian deep-learning mirror-neurons by vankov on 2016-05-22 21:10:19 along with 1 person Abstract
	✔ Deep Neural Networks as a Computational Model for Human Shape Sensitivity PLoS Comput Biol, Vol. 12, No. 4. (28 April 2016), e1004896, doi:10.1371/journal.pcbi.1004896 by Jonas Kubilius, Stefania Bracci, Hans P. Op de Beeck posted to caffe deep-learning image neuroscience perception by ajs625 on 2016-05-16 00:17:33 Abstract
	✔ Deep learning. Nature, Vol. 521, No. 7553. (28 May 2015), pp. 436-444 by Yann LeCun, Yoshua Bengio, Geoffrey Hinton posted to deep-learning by assafzar on 2016-05-15 23:08:36 along with 1 person Abstract Notes
	✔ Basset: Learning the regulatory code of the accessible genome with deep convolutional neural networks Genome Research (03 May 2016), gr.200535.115, doi:10.1101/gr.200535.115 by David R. Kelley, Jasper Snoek, John Rinn posted to deep-learning regulation by pickw on 2016-05-07 17:35:27 Abstract
	✔ Mastering the game of Go with deep neural networks and tree search Nature, Vol. 529, No. 7587. (28 January 2016), pp. 484-489, doi:10.1038/nature16961 by David Silver, Aja Huang, Chris J. Maddison, et al. posted to ai deep-learning neural-networks by vankov on 2016-05-05 12:53:35 along with 14 people
	✔ Deep Metric Learning via Lifted Structured Feature Embedding (19 Nov 2015) by Hyun O. Song, Yu Xiang, Stefanie Jegelka, Silvio Savarese posted to deep-learning by angli on 2016-05-02 20:01:33 Abstract
	✔ Convergent Learning: Do different neural networks learn the same representations? (28 Feb 2016) by Yixuan Li, Jason Yosinski, Jeff Clune, Hod Lipson, John Hopcroft posted to deep-learning feature image representation by ajs625 on 2016-04-28 21:34:26 Abstract
	✔ A Taxonomy of Deep Convolutional Neural Nets for Computer Vision Frontiers in Robotics and AI, Vol. 2 (25 Jan 2016), doi:10.3389/frobt.2015.00036 by Suraj Srinivas, Ravi K. Sarvadevabhatla, Konda R. Mopuri, Nikita Prabhu, Srinivas S. S. Kruthiventi, R. Venkatesh Babu posted to deep-learning todo vision by falex on 2016-04-27 08:44:51 Abstract
	✔ Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (2 Mar 2015) by Sergey Ioffe, Christian Szegedy posted to deep-learning by hans_meine on 2016-04-24 12:24:16 along with 6 people Abstract
	✔ Human-level control through deep reinforcement learning Nature, Vol. 518, No. 7540. (26 February 2015), pp. 529-533, doi:10.1038/nature14236 by Volodymyr Mnih, Koray Kavukcuoglu, David Silver, et al. posted to 2015 ai deep-learning game neural-network q-learning reinforcement-learning by ddahlem on 2016-04-22 13:37:41 along with 19 people and 2 groups
	✔ Adding Gradient Noise Improves Learning for Very Deep Networks (21 Nov 2015) by Arvind Neelakantan, Luke Vilnis, Quoc V. Le, et al. posted to deep-learning gradient neural-network statistical-learning by lehalle on 2016-04-10 17:54:43 Abstract
	The application of an ensemble of boosted Elman networks to time series prediction: a benchmark study J Comput Intell, Vol. 3, No. 2. (2005), pp. 119-126 by Chee P. Lim, Wei Y. Goh posted to arma cnn convnet deep-learning neural-network time-series by lehalle on 2016-04-06 11:13:01
	On the prediction of solar activity using different neural network models In Annales Geophysicae, Vol. 14, No. 1. (1996) by Francoise Fessant, Samy Bengio, Daniel Collobert posted to arma cnn compression convnet deep-learning neural-network time-series by lehalle on 2016-04-06 11:08:01
	✔ Identity Mappings in Deep Residual Networks (16 Mar 2016) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning dlws101 by hans_meine on 2016-04-01 21:08:03 Abstract
	✔ Deep Residual Learning for Image Recognition (10 Dec 2015) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning dlws101 by hans_meine on 2016-04-01 21:06:16 along with 5 people Abstract
	✔ Variational inference for Monte Carlo objectives (22 Feb 2016) by Andriy Mnih, Danilo J. Rezende posted to deep-learning latent-variable machine-learning mcmc statistics variational-bayes by memming on 2016-03-25 03:19:27 Abstract
	✔ Discriminative Regularization for Generative Models (15 Feb 2016) by Alex Lamb, Vincent Dumoulin, Aaron Courville posted to deep-learning math by mathkann on 2016-03-24 13:53:11 Abstract
	✔ The Loss Surfaces of Multilayer Networks (21 Jan 2015) by Anna Choromanska, Mikael Henaff, Michael Mathieu, Gérard B. Arous, Yann LeCun posted to deep-learning optimization by lehalle on 2016-03-24 09:55:07 along with 2 people Abstract
	✔ Explicit information for category-orthogonal object properties increases along the ventral stream Nat Neurosci, Vol. advance online publication (22 February 2016), doi:10.1038/nn.4247 by Ha Hong, Daniel L. K. Yamins, Najib J. Majaj, James J. DiCarlo posted to convolutional-model deep-learning it object-recognition ventral-stream by memming on 2016-03-21 20:40:19
	✔ Deep learning in neural networks: An overview Neural Networks, Vol. 61 (8 January 2015), pp. 85-117, doi:10.1016/j.neunet.2014.09.003 by Jürgen Schmidhuber posted to deep-learning review by pickw on 2016-03-15 01:17:12 along with 10 people and 1 group Abstract
	✔ Spatio-Temporal Signatures to Predict Retinal Disease Recurrence In Information Processing in Medical Imaging, Vol. 9123 (2015), pp. 152-163, doi:10.1007/978-3-319-19992-4_12 by Wolf-Dieter Vogl, SebastianM Waldstein, BiancaS Gerendas, et al. edited by Sebastien Ourselin, Daniel C. Alexander, Carl-Fredrik Westin, M. Jorge Cardoso posted to deep-learning by hans_meine on 2016-03-14 16:14:24
	✔ Learning Physical Intuition of Block Towers by Example (3 Mar 2016) by Adam Lerer, Sam Gross, Rob Fergus posted to ai deep-learning games by mathkann on 2016-03-10 06:53:40 Abstract
	✔ Dynamic Memory Networks for Visual and Textual Question Answering (4 Mar 2016) by Caiming Xiong, Stephen Merity, Richard Socher posted to ai deep-learning neural-networks by mathkann on 2016-03-09 07:18:36 along with 1 person Abstract
	✔ Mapping visual features to semantic profiles for retrieval in medical imaging In Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on (June 2015), pp. 457-465, doi:10.1109/cvpr.2015.7298643 by Johannes Hofmanninger, Georg Langs posted to deep-learning by hans_meine on 2016-03-04 13:28:46
	✔ Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets (1 Jun 2015) by Armand Joulin, Tomas Mikolov posted to deep-learning model sequence todo by falex on 2016-03-01 15:30:14 along with 2 people Abstract
	✔ Using goal-driven deep learning models to understand sensory cortex Nature Neuroscience, Vol. 19, No. 3. (23 February 2016), pp. 356-365, doi:10.1038/nn.4244 by Daniel L. K. Yamins, James J. DiCarlo posted to cortex deep-learning model todo vision by falex on 2016-02-29 15:57:40 along with 2 people
	✔ Black box variational inference for state space models (23 Nov 2015) by Evan Archer, Il M. Park, Lars Buesing, John Cunningham, Liam Paninski posted to deep-learning machine-learning stochastic-gradient-descent-algorithm time-series variational-bayes by memming on 2016-02-23 15:24:40 Abstract
	✔ Dropout: A Simple Way to Prevent Neural Networks from Overfitting J. Mach. Learn. Res., Vol. 15, No. 1. (January 2014), pp. 1929-1958 by Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov posted to deep-learning neural-network statistical-learning by martinzokov on 2016-02-20 01:00:47 along with 4 people and 1 group Abstract
	✔ Practical recommendations for gradient-based training of deep architectures (16 Sep 2012) by Yoshua Bengio posted to deep-learning statistical-learning by lehalle on 2016-02-12 22:02:07 along with 3 people Abstract
	✔ Exploring the Limits of Language Modeling (11 Feb 2016) by Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, Yonghui Wu posted to deep-learning nlp rnn by mathkann on 2016-02-09 12:22:03 along with 3 people Abstract
	✔ The Ebb and Flow of Deep Learning: a Theory of Local Learning (22 Jun 2015) by Pierre Baldi, Peter Sadowski posted to deep-learning local-learning-rule machine-learning theoretical-neuroscience by memming on 2016-01-13 16:31:15 Abstract
	✔ Continuous control with deep reinforcement learning (7 Jan 2016) by Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, et al. posted to continuous-control deep-learning model-based-rl reinforcement by memming on 2016-01-09 15:00:17 along with 2 people Abstract
	✔ Deep Learning for Content-Based Image Retrieval: A Comprehensive Study In Proceedings of the 22Nd ACM International Conference on Multimedia (2014), pp. 157-166, doi:10.1145/2647868.2654948 by Ji Wan, Dayong Wang, Steven Chu Hong Hoi, et al. posted to cbir deep-learning machine-learning review by ajs625 on 2016-01-07 20:54:41 Abstract
	✔ Deep learning of binary hash codes for fast image retrieval In Computer Vision and Pattern Recognition Workshops (CVPRW), 2015 IEEE Conference on (June 2015), pp. 27-35, doi:10.1109/cvprw.2015.7301269 by Kevin Lin, Huei-Fang Yang, Jen-Hao Hsiao, Chu-Song Chen posted to cbir deep-learning hashing image by ajs625 on 2016-01-07 20:52:02
	✔ Object Detectors Emerge in Deep Scene CNNs (15 Apr 2015) by Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba posted to computer-vision deep-learning by assafzar on 2015-12-30 15:47:11 Abstract
	✔ Automatic detection of cell divisions (mitosis) in live-imaging microscopy images using Convolutional Neural Networks In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (August 2015), pp. 743-746, doi:10.1109/embc.2015.7318469 by Anat Shkolyar, Amit Gefen, Dafna Benayahu, Hayit Greenspan posted to collective-cell-migration deep-learning by assafzar on 2015-12-30 15:39:03
	✔ Imagenet classification with deep convolutional neural networks In Advances in Neural Information Processing Systems, Vol. 25 (2012) by Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton posted to classification cnn cv deep-learning imagenet by ok1zjf on 2015-12-29 03:33:17 / along with 9 people Abstract
	✔ Learning Visual Predictive Models of Physics for Playing Billiards (23 Nov 2015) by Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, Jitendra Malik posted to computer-vision deep-learning iclr machine-learning physics video by memming on 2015-12-22 21:14:30 Abstract
	✔ Stacked Attention Networks for Image Question Answering (7 Nov 2015) by Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Smola posted to deep-learning image machine-learning machine-teaching speech by ajs625 on 2015-12-18 22:04:42 Abstract
	✔ Learning deep dynamical models from image pixels (28 Oct 2014) by Niklas Wahlström, Thomas B. Schön, Marc P. Deisenroth posted to autoencoder deep-learning image latent-dynamics nonlinear-systems time-series video by memming on 2015-12-16 16:40:37 Abstract
	✔ Hierarchical Variational Models (7 Nov 2015) by Rajesh Ranganath, Dustin Tran, David M. Blei posted to bayesian deep-learning inference-network machine-learning variational-bayes by memming on 2015-12-16 16:27:08 along with 1 person Abstract
	✔ Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (7 Jan 2016) by Alec Radford, Luke Metz, Soumith Chintala posted to adversarial-network cnn deep-learning iclr image by memming on 2015-12-16 16:21:20 along with 3 people Abstract
	✔ Variational Auto-encoded Deep Gaussian Processes (19 Nov 2015) by Zhenwen Dai, Andreas Damianou, Javier González, Neil Lawrence posted to autoencoder deep-gaussian-processes deep-learning gaussian-process iclr variational-bayes by memming on 2015-12-16 16:19:20 Abstract
	✔ Stochastic Optimization for Deep CCA via Nonlinear Orthogonal Iterations (7 Oct 2015) by Weiran Wang, Raman Arora, Karen Livescu, Nathan Srebro posted to cca deep-learning by memming on 2015-12-16 15:55:15 Abstract
	✔ Why are deep nets reversible: A simple theory, with implications for training (19 Nov 2015) by Sanjeev Arora, Yingyu Liang, Tengyu Ma posted to autoencoder deep-learning learning symmetry theoretical-neuroscience by memming on 2015-12-16 15:52:40 Abstract
	✔ Deep multi-scale video prediction beyond mean square error (23 Nov 2015) by Michael Mathieu, Camille Couprie, Yann LeCun posted to deep-learning machine-learning time-series video by memming on 2015-12-16 15:31:55 Abstract

续

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933 by Vincent Michalski, Roland Memisevic, Kishore Konda edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43
	✔ Unsupervised Learning of Video Representations using LSTMs (31 Mar 2015) by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54 along with 4 people Abstract
	✔ Better Computer Go Player with Neural Network and Long-term Prediction (26 Jan 2016) by Yuandong Tian, Yan Zhu posted to deep-learning games go by lehalle on 2015-12-09 17:57:52 along with 2 people Abstract
	✔ Fully Convolutional Networks for Semantic Segmentation (8 Mar 2015) by Jonathan Long, Evan Shelhamer, Trevor Darrell posted to deep-learning by hans_meine on 2015-12-04 19:12:45 along with 2 people Abstract Notes
	✔ Gradient Estimation Using Stochastic Computation Graphs (13 Nov 2015) by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 Abstract
	✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling (23 Sep 2015) by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 Abstract
	✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images (20 Nov 2015) by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21 along with 1 person Abstract
	✔ Variational Gaussian Process (20 Nov 2015) by Dustin Tran, Rajesh Ranganath, David M. Blei posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08 along with 1 person Abstract
	✔ SparkNet: Training Deep Networks in Spark (26 Nov 2015) by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30 along with 3 people Abstract
	✔ Deep Kalman Filters (16 Nov 2015) by Rahul G. Krishnan, Uri Shalit, David Sontag posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 Abstract
	✔ Sequence to Sequence Learning with Neural Networks (14 Dec 2014) by Ilya Sutskever, Oriol Vinyals, Quoc V. Le posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05 along with 4 people Abstract
	✔ Privacy-Preserving Deep Learning In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687 by Reza Shokri, Vitaly Shmatikov posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 Abstract
	✔ Predicting effects of noncoding variants with deep learning–based sequence model Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547 by Jian Zhou, Olga G. Troyanskaya posted to deep-learning functional-annotation non-coding by pickw on 2015-10-14 19:08:24 along with 8 people and 1 group
	✔ Curriculum Learning In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380 by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12 along with 2 people Abstract
	✔ High-order neural networks and kernel methods for peptide-MHC binding prediction Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371 by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein posted to deep-learning interaction machine-learning protein-protein by ajs625 on 2015-09-22 05:37:13 along with 1 person and 1 group Abstract
	✔ Deep Broad Learning - Big Models for Big Data (4 Sep 2015) by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 Abstract
	✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838 by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03 along with 1 person Abstract
	✔ A Neural Algorithm of Artistic Style (2 Sep 2015) by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59 along with 5 people Abstract
	✔ Quantum Deep Learning (22 May 2015) by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45 along with 2 people Abstract
	✔ Deep Learning for Single-View Instance Recognition (29 Jul 2015) by David Held, Sebastian Thrun, Silvio Savarese posted to deep-learning by noud88 on 2015-07-31 13:49:47 Abstract
	✔ Training Very Deep Networks (22 Jul 2015) by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber posted to deep-learning by mathkann on 2015-07-23 09:30:53 Abstract
	✔ Unsupervised Learning on Neural Network Outputs (7 Jul 2015) by Yao Lu posted to deep-learning by mathkann on 2015-07-08 14:23:44 Abstract
	✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding (29 May 2015) by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu posted to deep-learning by hukkinen on 2015-06-16 16:12:14 Abstract
	✔ Variational Inference with Normalizing Flows In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538 by Danilo J. Rezende, Shakir Mohamed posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 Abstract
	✔ Visualizing and Understanding Recurrent Networks (17 Nov 2015) by Andrej Karpathy, Justin Johnson, Li Fei-Fei posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34 along with 2 people Abstract
	✔ A Critical Review of Recurrent Neural Networks for Sequence Learning (29 Jun 2015) by Zachary C. Lipton posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02 along with 3 people Abstract
	✔ Blocks and Fuel: Frameworks for deep learning (1 Jun 2015) by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al. posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 Abstract
	Deep AutoRegressive Networks In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250 by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra edited by Tony Jebara, Eric P. Xing posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 Abstract
	✔ Building high-level features using large scale unsupervised learning In In International Conference on Machine Learning, 2012. 103 by Quoc V. Le, Rajat Monga, Matthieu Devin, et al. posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 Abstract
	✔ Reducing the dimensionality of data with neural networks. Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647 by G. E. Hinton, R. R. Salakhutdinov posted to deep-learning machine-learning print by falex on 2015-05-12 10:18:44 along with 50 people and 10 groups Abstract
	✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (6 Feb 2015) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning by mathkann on 2015-05-06 05:03:15 along with 3 people and 1 group Abstract
	✔ Low precision storage for deep learning (3 Apr 2015) by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David posted to deep-learning by mathkann on 2015-04-29 19:36:28 along with 1 person Abstract
	✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik posted to deep-learning by babakap on 2015-04-16 20:09:14 Abstract
	Theano: a CPU and GPU Math Expression Compiler In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010) by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al. posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58 along with 1 person Abstract
	✔ Theano: new features and speed improvements (23 Nov 2012) by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al. posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34 along with 3 people Abstract
	✔ Generative models for discovering sparse distributed representations Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101 by Geoffrey E. Hinton, Zoubin Ghahramani posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19 along with 4 people Abstract
	✔ On the Computational Efficiency of Training Neural Networks (28 Oct 2014) by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36 along with 3 people Abstract
	✔ Reweighted Wake-Sleep (11 Jun 2014) by Jörg Bornschein, Yoshua Bengio posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07 along with 1 person Abstract
	✔ Learning Stochastic Recurrent Networks (5 Mar 2015) by Justin Bayer, Christian Osendorfer posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42 along with 3 people Abstract
	✔ Towards Biologically Plausible Deep Learning (14 Feb 2015) by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15 along with 2 people Abstract
	✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years (31 Aug 2007) by Juergen Schmidhuber posted to agi deep-learning by chadwcarlson on 2015-04-12 11:17:52 along with 5 people and 1 group Abstract
	✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity (5 Sep 2007) by Juergen Schmidhuber posted to deep-learning machine-learning by chadwcarlson on 2015-04-12 11:17:21 along with 5 people and 2 groups Abstract
	✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3 by Tom Schaul, Leo Pape, Tobias Glasmachers, et al. edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40 along with 1 person Abstract
	✔ Visualizing and Understanding Convolutional Networks (28 Nov 2013) by Matthew D. Zeiler, Rob Fergus posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group Abstract
	✔ Greedy layer-wise training of deep networks In In NIPS (2007) by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, UniversitÃ© De MontrÃ©al, MontrÃ©al QuÃ©bec posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54 along with 10 people Abstract
	✔ Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53 along with 9 people and 1 group Abstract
	✔ Deep learning from temporal coherence in video In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469 by Hossein Mobahi, Ronan Collobert, Jason Weston posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35 along with 5 people Abstract
	✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units (7 Apr 2015) by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47 along with 1 person Abstract
	✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease. Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806 by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al. posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw on 2015-04-08 03:47:39 along with 22 people and 3 groups Abstract
	✔ Computational intelligence techniques in bioinformatics. Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47 by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 Abstract

Tag deep-learning [159 articles]

Recent papers classified by the tag deep-learning.

	Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933 by Vincent Michalski, Roland Memisevic, Kishore Konda edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43
	✔ Unsupervised Learning of Video Representations using LSTMs (31 Mar 2015) by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54 along with 4 people Abstract
	✔ Better Computer Go Player with Neural Network and Long-term Prediction (26 Jan 2016) by Yuandong Tian, Yan Zhu posted to deep-learning games go by lehalle on 2015-12-09 17:57:52 along with 2 people Abstract
	✔ Fully Convolutional Networks for Semantic Segmentation (8 Mar 2015) by Jonathan Long, Evan Shelhamer, Trevor Darrell posted to deep-learning by hans_meine on 2015-12-04 19:12:45 along with 2 people Abstract Notes
	✔ Gradient Estimation Using Stochastic Computation Graphs (13 Nov 2015) by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 Abstract
	✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling (23 Sep 2015) by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 Abstract
	✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images (20 Nov 2015) by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21 along with 1 person Abstract
	✔ Variational Gaussian Process (20 Nov 2015) by Dustin Tran, Rajesh Ranganath, David M. Blei posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08 along with 1 person Abstract
	✔ SparkNet: Training Deep Networks in Spark (26 Nov 2015) by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30 along with 3 people Abstract
	✔ Deep Kalman Filters (16 Nov 2015) by Rahul G. Krishnan, Uri Shalit, David Sontag posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 Abstract
	✔ Sequence to Sequence Learning with Neural Networks (14 Dec 2014) by Ilya Sutskever, Oriol Vinyals, Quoc V. Le posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05 along with 4 people Abstract
	✔ Privacy-Preserving Deep Learning In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687 by Reza Shokri, Vitaly Shmatikov posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 Abstract
	✔ Predicting effects of noncoding variants with deep learning–based sequence model Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547 by Jian Zhou, Olga G. Troyanskaya posted to deep-learning functional-annotation non-coding by pickw on 2015-10-14 19:08:24 along with 8 people and 1 group
	✔ Curriculum Learning In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380 by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12 along with 2 people Abstract
	✔ High-order neural networks and kernel methods for peptide-MHC binding prediction Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371 by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein posted to deep-learning interaction machine-learning protein-protein by ajs625 on 2015-09-22 05:37:13 along with 1 person and 1 group Abstract
	✔ Deep Broad Learning - Big Models for Big Data (4 Sep 2015) by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 Abstract
	✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838 by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03 along with 1 person Abstract
	✔ A Neural Algorithm of Artistic Style (2 Sep 2015) by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59 along with 5 people Abstract
	✔ Quantum Deep Learning (22 May 2015) by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45 along with 2 people Abstract
	✔ Deep Learning for Single-View Instance Recognition (29 Jul 2015) by David Held, Sebastian Thrun, Silvio Savarese posted to deep-learning by noud88 on 2015-07-31 13:49:47 Abstract
	✔ Training Very Deep Networks (22 Jul 2015) by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber posted to deep-learning by mathkann on 2015-07-23 09:30:53 Abstract
	✔ Unsupervised Learning on Neural Network Outputs (7 Jul 2015) by Yao Lu posted to deep-learning by mathkann on 2015-07-08 14:23:44 Abstract
	✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding (29 May 2015) by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu posted to deep-learning by hukkinen on 2015-06-16 16:12:14 Abstract
	✔ Variational Inference with Normalizing Flows In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538 by Danilo J. Rezende, Shakir Mohamed posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 Abstract
	✔ Visualizing and Understanding Recurrent Networks (17 Nov 2015) by Andrej Karpathy, Justin Johnson, Li Fei-Fei posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34 along with 2 people Abstract
	✔ A Critical Review of Recurrent Neural Networks for Sequence Learning (29 Jun 2015) by Zachary C. Lipton posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02 along with 3 people Abstract
	✔ Blocks and Fuel: Frameworks for deep learning (1 Jun 2015) by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al. posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 Abstract
	Deep AutoRegressive Networks In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250 by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra edited by Tony Jebara, Eric P. Xing posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 Abstract
	✔ Building high-level features using large scale unsupervised learning In In International Conference on Machine Learning, 2012. 103 by Quoc V. Le, Rajat Monga, Matthieu Devin, et al. posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 Abstract
	✔ Reducing the dimensionality of data with neural networks. Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647 by G. E. Hinton, R. R. Salakhutdinov posted to deep-learning machine-learning print by falex on 2015-05-12 10:18:44 along with 50 people and 10 groups Abstract
	✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (6 Feb 2015) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning by mathkann on 2015-05-06 05:03:15 along with 3 people and 1 group Abstract
	✔ Low precision storage for deep learning (3 Apr 2015) by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David posted to deep-learning by mathkann on 2015-04-29 19:36:28 along with 1 person Abstract
	✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik posted to deep-learning by babakap on 2015-04-16 20:09:14 Abstract
	Theano: a CPU and GPU Math Expression Compiler In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010) by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al. posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58 along with 1 person Abstract
	✔ Theano: new features and speed improvements (23 Nov 2012) by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al. posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34 along with 3 people Abstract
	✔ Generative models for discovering sparse distributed representations Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101 by Geoffrey E. Hinton, Zoubin Ghahramani posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19 along with 4 people Abstract
	✔ On the Computational Efficiency of Training Neural Networks (28 Oct 2014) by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36 along with 3 people Abstract
	✔ Reweighted Wake-Sleep (11 Jun 2014) by Jörg Bornschein, Yoshua Bengio posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07 along with 1 person Abstract
	✔ Learning Stochastic Recurrent Networks (5 Mar 2015) by Justin Bayer, Christian Osendorfer posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42 along with 3 people Abstract
	✔ Towards Biologically Plausible Deep Learning (14 Feb 2015) by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15 along with 2 people Abstract
	✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years (31 Aug 2007) by Juergen Schmidhuber posted to agi deep-learning by chadwcarlson on 2015-04-12 11:17:52 along with 5 people and 1 group Abstract
	✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity (5 Sep 2007) by Juergen Schmidhuber posted to deep-learning machine-learning by chadwcarlson on 2015-04-12 11:17:21 along with 5 people and 2 groups Abstract
	✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3 by Tom Schaul, Leo Pape, Tobias Glasmachers, et al. edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40 along with 1 person Abstract
	✔ Visualizing and Understanding Convolutional Networks (28 Nov 2013) by Matthew D. Zeiler, Rob Fergus posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group Abstract
	✔ Greedy layer-wise training of deep networks In In NIPS (2007) by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, UniversitÃ© De MontrÃ©al, MontrÃ©al QuÃ©bec posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54 along with 10 people Abstract
	✔ Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53 along with 9 people and 1 group Abstract
	✔ Deep learning from temporal coherence in video In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469 by Hossein Mobahi, Ronan Collobert, Jason Weston posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35 along with 5 people Abstract
	✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units (7 Apr 2015) by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47 along with 1 person Abstract
	✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease. Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806 by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al. posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw on 2015-04-08 03:47:39 along with 22 people and 3 groups Abstract
	✔ Computational intelligence techniques in bioinformatics. Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47 by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 Abstract

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933 by Vincent Michalski, Roland Memisevic, Kishore Konda edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43
	✔ Unsupervised Learning of Video Representations using LSTMs (31 Mar 2015) by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54 along with 4 people Abstract
	✔ Better Computer Go Player with Neural Network and Long-term Prediction (26 Jan 2016) by Yuandong Tian, Yan Zhu posted to deep-learning games go by lehalle on 2015-12-09 17:57:52 along with 2 people Abstract
	✔ Fully Convolutional Networks for Semantic Segmentation (8 Mar 2015) by Jonathan Long, Evan Shelhamer, Trevor Darrell posted to deep-learning by hans_meine on 2015-12-04 19:12:45 along with 2 people Abstract Notes
	✔ Gradient Estimation Using Stochastic Computation Graphs (13 Nov 2015) by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 Abstract
	✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling (23 Sep 2015) by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 Abstract
	✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images (20 Nov 2015) by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21 along with 1 person Abstract
	✔ Variational Gaussian Process (20 Nov 2015) by Dustin Tran, Rajesh Ranganath, David M. Blei posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08 along with 1 person Abstract
	✔ SparkNet: Training Deep Networks in Spark (26 Nov 2015) by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30 along with 3 people Abstract
	✔ Deep Kalman Filters (16 Nov 2015) by Rahul G. Krishnan, Uri Shalit, David Sontag posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 Abstract
	✔ Sequence to Sequence Learning with Neural Networks (14 Dec 2014) by Ilya Sutskever, Oriol Vinyals, Quoc V. Le posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05 along with 4 people Abstract
	✔ Privacy-Preserving Deep Learning In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687 by Reza Shokri, Vitaly Shmatikov posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 Abstract
	✔ Predicting effects of noncoding variants with deep learning–based sequence model Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547 by Jian Zhou, Olga G. Troyanskaya posted to deep-learning functional-annotation non-coding by pickw on 2015-10-14 19:08:24 along with 8 people and 1 group
	✔ Curriculum Learning In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380 by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12 along with 2 people Abstract
	✔ High-order neural networks and kernel methods for peptide-MHC binding prediction Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371 by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein posted to deep-learning interaction machine-learning protein-protein by ajs625 on 2015-09-22 05:37:13 along with 1 person and 1 group Abstract
	✔ Deep Broad Learning - Big Models for Big Data (4 Sep 2015) by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 Abstract
	✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838 by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03 along with 1 person Abstract
	✔ A Neural Algorithm of Artistic Style (2 Sep 2015) by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59 along with 5 people Abstract
	✔ Quantum Deep Learning (22 May 2015) by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45 along with 2 people Abstract
	✔ Deep Learning for Single-View Instance Recognition (29 Jul 2015) by David Held, Sebastian Thrun, Silvio Savarese posted to deep-learning by noud88 on 2015-07-31 13:49:47 Abstract
	✔ Training Very Deep Networks (22 Jul 2015) by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber posted to deep-learning by mathkann on 2015-07-23 09:30:53 Abstract
	✔ Unsupervised Learning on Neural Network Outputs (7 Jul 2015) by Yao Lu posted to deep-learning by mathkann on 2015-07-08 14:23:44 Abstract
	✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding (29 May 2015) by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu posted to deep-learning by hukkinen on 2015-06-16 16:12:14 Abstract
	✔ Variational Inference with Normalizing Flows In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538 by Danilo J. Rezende, Shakir Mohamed posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 Abstract
	✔ Visualizing and Understanding Recurrent Networks (17 Nov 2015) by Andrej Karpathy, Justin Johnson, Li Fei-Fei posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34 along with 2 people Abstract
	✔ A Critical Review of Recurrent Neural Networks for Sequence Learning (29 Jun 2015) by Zachary C. Lipton posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02 along with 3 people Abstract
	✔ Blocks and Fuel: Frameworks for deep learning (1 Jun 2015) by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al. posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 Abstract
	Deep AutoRegressive Networks In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250 by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra edited by Tony Jebara, Eric P. Xing posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 Abstract
	✔ Building high-level features using large scale unsupervised learning In In International Conference on Machine Learning, 2012. 103 by Quoc V. Le, Rajat Monga, Matthieu Devin, et al. posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 Abstract
	✔ Reducing the dimensionality of data with neural networks. Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647 by G. E. Hinton, R. R. Salakhutdinov posted to deep-learning machine-learning print by falex on 2015-05-12 10:18:44 along with 50 people and 10 groups Abstract
	✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (6 Feb 2015) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning by mathkann on 2015-05-06 05:03:15 along with 3 people and 1 group Abstract
	✔ Low precision storage for deep learning (3 Apr 2015) by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David posted to deep-learning by mathkann on 2015-04-29 19:36:28 along with 1 person Abstract
	✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik posted to deep-learning by babakap on 2015-04-16 20:09:14 Abstract
	Theano: a CPU and GPU Math Expression Compiler In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010) by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al. posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58 along with 1 person Abstract
	✔ Theano: new features and speed improvements (23 Nov 2012) by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al. posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34 along with 3 people Abstract
	✔ Generative models for discovering sparse distributed representations Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101 by Geoffrey E. Hinton, Zoubin Ghahramani posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19 along with 4 people Abstract
	✔ On the Computational Efficiency of Training Neural Networks (28 Oct 2014) by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36 along with 3 people Abstract
	✔ Reweighted Wake-Sleep (11 Jun 2014) by Jörg Bornschein, Yoshua Bengio posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07 along with 1 person Abstract
	✔ Learning Stochastic Recurrent Networks (5 Mar 2015) by Justin Bayer, Christian Osendorfer posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42 along with 3 people Abstract
	✔ Towards Biologically Plausible Deep Learning (14 Feb 2015) by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15 along with 2 people Abstract
	✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years (31 Aug 2007) by Juergen Schmidhuber posted to agi deep-learning by chadwcarlson on 2015-04-12 11:17:52 along with 5 people and 1 group Abstract
	✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity (5 Sep 2007) by Juergen Schmidhuber posted to deep-learning machine-learning by chadwcarlson on 2015-04-12 11:17:21 along with 5 people and 2 groups Abstract
	✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3 by Tom Schaul, Leo Pape, Tobias Glasmachers, et al. edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40 along with 1 person Abstract
	✔ Visualizing and Understanding Convolutional Networks (28 Nov 2013) by Matthew D. Zeiler, Rob Fergus posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group Abstract
	✔ Greedy layer-wise training of deep networks In In NIPS (2007) by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, UniversitÃ© De MontrÃ©al, MontrÃ©al QuÃ©bec posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54 along with 10 people Abstract
	✔ Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53 along with 9 people and 1 group Abstract
	✔ Deep learning from temporal coherence in video In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469 by Hossein Mobahi, Ronan Collobert, Jason Weston posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35 along with 5 people Abstract
	✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units (7 Apr 2015) by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47 along with 1 person Abstract
	✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease. Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806 by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al. posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw on 2015-04-08 03:47:39 along with 22 people and 3 groups Abstract
	✔ Computational intelligence techniques in bioinformatics. Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47 by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 Abstract

Tag deep-learning [159 articles]

Recent papers classified by the tag deep-learning.

	✔ Exact solutions to the nonlinear dynamics of learning in deep linear neural networks (19 Feb 2014) by Andrew M. Saxe, James L. McClelland, Surya Ganguli posted to deep-learning dynamical-system machine-learning optimization by memming on 2015-03-22 21:30:05 Abstract
	✔ DRAW: A Recurrent Neural Network For Image Generation (20 May 2015) by Karol Gregor, Ivo Danihelka, Alex Graves, Danilo J. Rezende, Daan Wierstra posted to deep-learning by mathkann on 2015-03-21 04:25:29 along with 4 people Abstract
	✔ An exact mapping between the Variational Renormalization Group and Deep Learning (14 Oct 2014) by Pankaj Mehta, David J. Schwab posted to deep-learning machine-learning physics renormalization-group by memming on 2015-03-20 18:27:55 along with 3 people Abstract
	✔ Complexity of random smooth functions on the high-dimensional sphere The Annals of Probability, Vol. 41, No. 6. (16 Dec 2013), pp. 4214-4247, doi:10.1214/13-aop862 by Antonio Auffinger, Gerard B. Arous posted to deep-learning high-dimension machine-learning statistics by memming on 2015-03-20 16:17:30 Abstract
	Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream In Advances in Neural Information Processing Systems 26 (2013), pp. 3093-3101 by Daniel L. Yamins, Ha Hong, Charles Cadieu, James J. DiCarlo edited by C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, K. Q. Weinberger posted to convolutional-neural-network deep-learning by memming on 2015-03-10 20:15:21 along with 1 person
	Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures In Proceedings of the 30th International Conference on Machine Learning, {ICML} 2013, Atlanta, GA, USA, 16-21 June 2013 (2013), pp. 115-123 by James Bergstra, Daniel Yamins, David D. Cox posted to deep-learning optimization by memming on 2015-03-10 20:04:49
	✔ Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project Drug Discovery Today, Vol. 20, No. 5. (May 2015), pp. 505-513, doi:10.1016/j.drudis.2014.12.014 by Bie Verbist, Günter Klambauer, Liesbet Vervoort, et al. posted to deep-learning drug-discovery by mathkann on 2015-02-20 14:56:42 along with 2 people Abstract
	✔ Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings (12 Feb 2015) by Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski posted to deep-learning nlp by mathkann on 2015-02-18 10:03:29 Abstract
	✔ Multi-view Face Detection Using Deep Convolutional Neural Networks (10 Feb 2015) by Sachin S. Farfade, Mohammad Saberian, Li-Jia Li posted to deep-learning by mathkann on 2015-02-17 14:55:40 along with 1 person Abstract
	✔ Large-Scale Deep Learning on the YFCC100M Dataset (11 Feb 2015) by Karl Ni, Roger Pearce, Kofi Boakye, et al. posted to deep-learning gpu hpc by mathkann on 2015-02-14 03:05:06 Abstract
	✔ Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images (2 Apr 2015) by Anh Nguyen, Jason Yosinski, Jeff Clune posted to convolutional-model deep-learning image-classification by memming on 2015-01-28 17:05:44 along with 5 people and 1 group Abstract
	✔ Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription (27 Jun 2012) by Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent posted to deep-learning discrete latent-dynamics music by memming on 2015-01-08 21:41:48 along with 2 people Abstract
	✔ How to Construct Deep Recurrent Neural Networks (24 Apr 2014) by Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio posted to deep-learning recurrent-neural-networks by raulsierra on 2014-12-17 00:36:36 along with 1 person Abstract
	✔ A Fast Learning Algorithm for Deep Belief Nets Neural Computation, Vol. 18, No. 7. (17 May 2006), pp. 1527-1554, doi:10.1162/neco.2006.18.7.1527 by Geoffrey E. Hinton, Simon Osindero, Yee-Whye Teh posted to deep-learning feature-learning by raulsierra on 2014-12-17 00:34:16 along with 29 people Abstract
	Doubly Stochastic Variational Bayes for non-Conjugate Inference In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1971-1979 by Michalis Titsias, Miguel Lázaro-gredilla edited by Tony Jebara, Eric P. Xing posted to deep-learning machine-learning variational-bayes by memming on 2014-12-13 17:12:17 along with 1 person Abstract
	✔ Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation Neural Computation, Vol. 22, No. 2. (18 November 2009), pp. 511-538, doi:10.1162/neco.2009.10-08-881 by Srinivas C. Turaga, Joseph F. Murray, Viren Jain, et al. posted to deep-learning hyperspectral-images image-segmentation by raulsierra on 2014-12-02 16:04:14 along with 4 people Abstract
	✔ Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion J. Mach. Learn. Res., Vol. 11 (December 2010), pp. 3371-3408 by Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre A. Manzagol posted to autoencoder deep-learning machine-learning manifold-learning unsupervised-learning by memming on 2014-11-10 15:13:25 Abstract
	✔ Extracting and Composing Robust Features with Denoising Autoencoders In Proceedings of the 25th International Conference on Machine Learning (2008), pp. 1096-1103, doi:10.1145/1390156.1390294 by Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre A. Manzagol posted to auto-encoder deep-learning icml manifold-learning robust by memming on 2014-10-27 22:38:26 along with 7 people Abstract
	✔ Emergence of a 'visual number sense' in hierarchical generative models Nat Neurosci, Vol. 15, No. 2. (8 February 2012), pp. 194-196, doi:10.1038/nn.2996 by Ivilin Stoianov, Marco Zorzi posted to deep-learning numerosity perception by memming on 2014-10-22 22:24:22 along with 3 people
	Deep learning via Hessian-free optimization In Proceedings of the 27th International Conference on Machine Learning (ICML-10) (June 2010), pp. 735-742 by James Martens edited by Johannes Fürnkranz, Thorsten Joachims posted to deep-learning hessian newton-method optimization by memming on 2014-10-19 00:44:24
	Generalized Denoising Auto-Encoders as Generative Models In Advances in Neural Information Processing Systems 26 (2013), pp. 899-907 by Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent edited by C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, K. Q. Weinberger posted to auto-encoder deep-learning machine-learning robust by memming on 2014-10-19 00:23:18
	✔ Identifying and attacking the saddle point problem in high-dimensional non-convex optimization (10 Jun 2014) by Yann Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio posted to deep-learning machine-learning newton-method optimization by memming on 2014-10-19 00:01:22 along with 4 people Abstract
	✔ Stochastic Backpropagation and Approximate Inference in Deep Generative Models In International Conference on Machine Learning (30 May 2014) by Danilo J. Rezende, Shakir Mohamed, Daan Wierstra posted to deep-learning machine-learning stochastic-gradient-descent-algorithm tricks variational-bayes by memming on 2014-10-12 22:12:06 along with 3 people Abstract
	Deep boltzmann machines In International Conference on Artificial Intelligence and Statistics (2009), pp. 448-455 by Ruslan Salakhutdinov, Geoffrey E. Hinton posted to botlzmann-machine deep-learning graph network neural-network statistica-learning by lehalle on 2014-09-26 09:32:43
	✔ TBCNN: A Tree-Based Convolutional Neural Network for Programming Language Processing (18 Sep 2014) by Lili Mou, Ge Li, Zhi Jin, Lu Zhang, Tao Wang posted to deep-learning neural-networks program-analysis program-comprehension by klerisson to the group LASCAM on 2014-09-22 14:42:05 Abstract
	✔ Building Program Vector Representations for Deep Learning (11 Sep 2014) by Lili Mou, Ge Li, Yuxuan Liu, et al. posted to classifier-learning deep-learning program-analysis program-comprehension by klerisson to the group LASCAM on 2014-09-17 15:37:16 Abstract
	✔ Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives (24 Jun 2012) by Yoshua Bengio, Aaron Courville, Pascal Vincent posted to deep-learning feature learning unsupervised by daltonwhyte on 2014-09-04 21:05:39 along with 1 person Abstract
	✔ Efficient Estimation of Word Representations in Vector Space (7 Sep 2013) by Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean posted to ann bow deep-learning lm ngram skipgram by lamafan on 2014-09-02 18:03:08 / along with 7 people Abstract
	✔ How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation (29 Jul 2014) by Yoshua Bengio posted to artificial-neural-network auto-encoder deep-learning machine-learning by memming on 2014-08-14 21:16:42 Abstract
	✔ Improving neural networks by preventing co-adaptation of feature detectors (3 Jul 2012) by Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, Ruslan R. Salakhutdinov posted to artificial-neural-network deep-learning machine-learning neural-network statistical-learning by lehalle on 2014-07-21 16:29:40 / along with 9 people Abstract
	Large scale online learning Advances in neural information processing systems, Vol. 16 (2004) by Leon B. Le Cun, L. Bottou posted to convergence deep-learning machine-learning perceptron by lehalle on 2014-07-13 18:22:07
	Deep learning made easier by linear transformations in perceptrons In International Conference on Artificial Intelligence and Statistics (2012), pp. 924-932 by Tapani Raiko, Harri Valpola, Yann LeCun posted to deep-learning machine-learning perceptron by lehalle on 2014-07-13 18:19:46
	✔ Event-driven contrastive divergence for spiking neuromorphic systems Frontiers in Neuroscience, Vol. 7 (2014), doi:10.3389/fnins.2013.00272 by Emre Neftci, Srinjoy Das, Bruno Pedroni, Kenneth Kreutz-Delgado, Gert Cauwenberghs posted to deep-learning neuromorphic-engineering sampling-hypothesis stdp by memming on 2014-02-03 21:46:46
	✔ Two Distributed-State Models For Generating High-Dimensional Time Series J. Mach. Learn. Res., Vol. 12 (July 2011), pp. 1025-1068 by Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis posted to deep-learning restricted-boltzmann-machine time-series by memming on 2014-01-28 17:17:38 Abstract
	✔ Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 1025-1032, doi:10.1145/1553374.1553505 by Graham W. Taylor, Geoffrey E. Hinton posted to deep-learning dynamical-system time-series by memming on 2014-01-28 17:09:04 along with 3 people Abstract
	✔ Automated processing and identification of benthic invertebrate samples Journal of the North American Benthological Society, Vol. 29, No. 3. (8 June 2010), pp. 867-874, doi:10.1899/09-080.1 by David A. Lytle, Gonzalo Martínez-Muñoz, Wei Zhang, et al. posted to deep-learning ecoinformatics feature-learning machine-learning by raulsierra on 2014-01-17 16:29:43 Abstract
	Rectified linear units improve restricted boltzmann machines In Proceedings of the 27th International Conference on Machine Learning (ICML-10) (2010), pp. 807-814 by Vinod Nair, Geoffrey E. Hinton posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:19:16
	Improving Deep Neural Networks for LVCSR using Rectified Linear Units and Dropout In Proc. ICASSP (2013) by George E. Dahl, Tara N. Sainath, Geoffrey E. Hinton posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:18:24
	Deep learning via Hessian-free optimization In Proceedings of the 27th International Conference on Machine Learning (ICML-10) (2010), pp. 735-742 by James Martens posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:17:21
	✔ Why Does Unsupervised Pre-training Help Deep Learning? J. Mach. Learn. Res., Vol. 11 (March 2010), pp. 625-660 by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre A. Manzagol, Pascal Vincent, Samy Bengio posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:16:28 along with 3 people Abstract
	Greedy layer-wise training of deep networks Advances in neural information processing systems, Vol. 19 (2007) by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:13:36
	✔ Representation Learning: A Review and New Perspectives Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 35, No. 8. (August 2013), pp. 1798-1828, doi:10.1109/tpami.2013.50 by Yoshua Bengio, Aaron C. Courville, Pascal Vincent posted to deep-learning machine-learning review todo by falex on 2013-08-17 18:43:26 along with 4 people and 1 group Abstract
	✔ To Recognize Shapes, First Learn to Generate Images Progress in Brain Research, Vol. 165 (2007), pp. 535-547, doi:10.1016/s0079-6123(06)65034-6 by Geoffrey E. Hinton posted to deep-learning by tatome on 2013-08-15 01:58:43 along with 3 people Abstract
	✔ Feature learning and deep architectures: new directions for music informatics In Journal of Intelligent Information Systems, Vol. 41, No. 3. (2013), pp. 461-481, doi:10.1007/s10844-013-0248-5 by EricJ Humphrey, JuanP Bello, Yann LeCun posted to deep-learning by craffel on 2013-07-16 18:03:49 along with 3 people Abstract
	✔ Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors (16 Mar 2013) by Danqi Chen, Richard Socher, Christopher D. Manning, Andrew Y. Ng posted to deep-learning by pengli09 on 2013-05-07 13:18:12 Abstract
	✔ Bayesian models: the structure of the world, uncertainty, behavior, and the brain: Bayesian models and the world Annals of the New York Academy of Sciences, Vol. 1224, No. 1. (April 2011), pp. 22-39, doi:10.1111/j.1749-6632.2011.05965.x by Iris Vilares, Konrad Kording posted to bayesian brain deep-learning information-theory model statistics by garyfeng to the group ReadingLab on 2013-04-10 02:36:23 along with 5 people Abstract
	✔ Building high-level features using large scale unsupervised learning (12 Jul 2012) by Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, et al. posted to computer_vision deep-learning feature-detection image_recognition machine-learning unsupervised-learning by tomhebbron on 2013-03-12 01:06:30 along with 11 people Abstract
	✔ Representation Learning: A Review and New Perspectives (23 Apr 2014) by Yoshua Bengio, Aaron Courville, Pascal Vincent posted to deep-learning machine-learning review by tomhebbron on 2013-03-11 19:36:25 along with 13 people and 1 group Abstract
	Large Scale Distributed Deep Networks In Advances in Neural Information Processing Systems 25 (2012) by Jeffrey Dea, Greg S. Corrado, Rajat Monga, et al. posted to 2012 bfgs deep-learning deeplearning google l-nfgs lbfgs nips sgd by myui on 2012-12-07 06:10:41 along with 2 people
	✔ Falsificationism and Statistical Learning Theory: Comparing the Popper and Vapnik-Chervonenkis Dimensions Journal for General Philosophy of Science, Vol. 40, No. 1. (20 August 2009), pp. 51-58, doi:10.1007/s10838-009-9091-3 by David Corfield, Bernhard Schölkopf, Vladimir Vapnik posted to deep-learning machine-learning philosophy-of-science statistics by tomhebbron on 2012-11-04 00:18:40 along with 1 person Abstract

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933 by Vincent Michalski, Roland Memisevic, Kishore Konda edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43
	✔ Unsupervised Learning of Video Representations using LSTMs (31 Mar 2015) by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54 along with 4 people Abstract
	✔ Better Computer Go Player with Neural Network and Long-term Prediction (26 Jan 2016) by Yuandong Tian, Yan Zhu posted to deep-learning games go by lehalle on 2015-12-09 17:57:52 along with 2 people Abstract
	✔ Fully Convolutional Networks for Semantic Segmentation (8 Mar 2015) by Jonathan Long, Evan Shelhamer, Trevor Darrell posted to deep-learning by hans_meine on 2015-12-04 19:12:45 along with 2 people Abstract Notes
	✔ Gradient Estimation Using Stochastic Computation Graphs (13 Nov 2015) by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 Abstract
	✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling (23 Sep 2015) by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 Abstract
	✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images (20 Nov 2015) by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21 along with 1 person Abstract
	✔ Variational Gaussian Process (20 Nov 2015) by Dustin Tran, Rajesh Ranganath, David M. Blei posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08 along with 1 person Abstract
	✔ SparkNet: Training Deep Networks in Spark (26 Nov 2015) by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30 along with 3 people Abstract
	✔ Deep Kalman Filters (16 Nov 2015) by Rahul G. Krishnan, Uri Shalit, David Sontag posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 Abstract
	✔ Sequence to Sequence Learning with Neural Networks (14 Dec 2014) by Ilya Sutskever, Oriol Vinyals, Quoc V. Le posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05 along with 4 people Abstract
	✔ Privacy-Preserving Deep Learning In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687 by Reza Shokri, Vitaly Shmatikov posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 Abstract
	✔ Predicting effects of noncoding variants with deep learning–based sequence model Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547 by Jian Zhou, Olga G. Troyanskaya posted to deep-learning functional-annotation non-coding by pickw on 2015-10-14 19:08:24 along with 8 people and 1 group
	✔ Curriculum Learning In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380 by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12 along with 2 people Abstract
	✔ High-order neural networks and kernel methods for peptide-MHC binding prediction Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371 by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein posted to deep-learning interaction machine-learning protein-protein by ajs625 on 2015-09-22 05:37:13 along with 1 person and 1 group Abstract
	✔ Deep Broad Learning - Big Models for Big Data (4 Sep 2015) by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 Abstract
	✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838 by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03 along with 1 person Abstract
	✔ A Neural Algorithm of Artistic Style (2 Sep 2015) by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59 along with 5 people Abstract
	✔ Quantum Deep Learning (22 May 2015) by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45 along with 2 people Abstract
	✔ Deep Learning for Single-View Instance Recognition (29 Jul 2015) by David Held, Sebastian Thrun, Silvio Savarese posted to deep-learning by noud88 on 2015-07-31 13:49:47 Abstract
	✔ Training Very Deep Networks (22 Jul 2015) by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber posted to deep-learning by mathkann on 2015-07-23 09:30:53 Abstract
	✔ Unsupervised Learning on Neural Network Outputs (7 Jul 2015) by Yao Lu posted to deep-learning by mathkann on 2015-07-08 14:23:44 Abstract
	✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding (29 May 2015) by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu posted to deep-learning by hukkinen on 2015-06-16 16:12:14 Abstract
	✔ Variational Inference with Normalizing Flows In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538 by Danilo J. Rezende, Shakir Mohamed posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 Abstract
	✔ Visualizing and Understanding Recurrent Networks (17 Nov 2015) by Andrej Karpathy, Justin Johnson, Li Fei-Fei posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34 along with 2 people Abstract
	✔ A Critical Review of Recurrent Neural Networks for Sequence Learning (29 Jun 2015) by Zachary C. Lipton posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02 along with 3 people Abstract
	✔ Blocks and Fuel: Frameworks for deep learning (1 Jun 2015) by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al. posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 Abstract
	Deep AutoRegressive Networks In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250 by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra edited by Tony Jebara, Eric P. Xing posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 Abstract
	✔ Building high-level features using large scale unsupervised learning In In International Conference on Machine Learning, 2012. 103 by Quoc V. Le, Rajat Monga, Matthieu Devin, et al. posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 Abstract
	✔ Reducing the dimensionality of data with neural networks. Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647 by G. E. Hinton, R. R. Salakhutdinov posted to deep-learning machine-learning print by falex on 2015-05-12 10:18:44 along with 50 people and 10 groups Abstract
	✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (6 Feb 2015) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning by mathkann on 2015-05-06 05:03:15 along with 3 people and 1 group Abstract
	✔ Low precision storage for deep learning (3 Apr 2015) by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David posted to deep-learning by mathkann on 2015-04-29 19:36:28 along with 1 person Abstract
	✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik posted to deep-learning by babakap on 2015-04-16 20:09:14 Abstract
	Theano: a CPU and GPU Math Expression Compiler In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010) by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al. posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58 along with 1 person Abstract
	✔ Theano: new features and speed improvements (23 Nov 2012) by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al. posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34 along with 3 people Abstract
	✔ Generative models for discovering sparse distributed representations Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101 by Geoffrey E. Hinton, Zoubin Ghahramani posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19 along with 4 people Abstract
	✔ On the Computational Efficiency of Training Neural Networks (28 Oct 2014) by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36 along with 3 people Abstract
	✔ Reweighted Wake-Sleep (11 Jun 2014) by Jörg Bornschein, Yoshua Bengio posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07 along with 1 person Abstract
	✔ Learning Stochastic Recurrent Networks (5 Mar 2015) by Justin Bayer, Christian Osendorfer posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42 along with 3 people Abstract
	✔ Towards Biologically Plausible Deep Learning (14 Feb 2015) by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15 along with 2 people Abstract
	✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years (31 Aug 2007) by Juergen Schmidhuber posted to agi deep-learning by chadwcarlson on 2015-04-12 11:17:52 along with 5 people and 1 group Abstract
	✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity (5 Sep 2007) by Juergen Schmidhuber posted to deep-learning machine-learning by chadwcarlson on 2015-04-12 11:17:21 along with 5 people and 2 groups Abstract
	✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3 by Tom Schaul, Leo Pape, Tobias Glasmachers, et al. edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40 along with 1 person Abstract
	✔ Visualizing and Understanding Convolutional Networks (28 Nov 2013) by Matthew D. Zeiler, Rob Fergus posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group Abstract
	✔ Greedy layer-wise training of deep networks In In NIPS (2007) by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, UniversitÃ© De MontrÃ©al, MontrÃ©al QuÃ©bec posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54 along with 10 people Abstract
	✔ Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53 along with 9 people and 1 group Abstract
	✔ Deep learning from temporal coherence in video In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469 by Hossein Mobahi, Ronan Collobert, Jason Weston posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35 along with 5 people Abstract
	✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units (7 Apr 2015) by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47 along with 1 person Abstract
	✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease. Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806 by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al. posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw on 2015-04-08 03:47:39 along with 22 people and 3 groups Abstract
	✔ Computational intelligence techniques in bioinformatics. Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47 by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 Abstract

Tag deep-learning [159 articles]

Recent papers classified by the tag deep-learning.

	Cooperative Learning and Soft Skills Training in an IT Course. Journal of Information Technology Education, Vol. 11 (January 2012), pp. 65-79 by Aimao Zhang, Louise Spiteri posted to collaborative-learning course-design deep-learning group-work-in-education information-technology information-technology----study-teaching-higher peer-assessment research soft-skills teaching-methods----research universities-colleges----curricula by jxchryst on 2012-10-24 13:18:23 Abstract Notes
	✔ Rapid Feature Learning with Stacked Linear Denoisers (5 May 2011) by Zhixiang E. Xu, Kilian Q. Weinberger, Fei Sha posted to classification deep-learning machine-learning svm unsupervised-learning by tomhebbron on 2012-08-20 13:10:49 Abstract
	✔ Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier] Computational Intelligence Magazine, IEEE, Vol. 5, No. 4. (November 2010), pp. 13-18, doi:10.1109/mci.2010.938364 by Itamar Arel, Derek C. Rose, T. P. Karnowski posted to deep-learning review by tomhebbron on 2012-06-25 20:10:22 along with 5 people Abstract
	✔ Learning Deep Architectures for AI Foundations and Trends® in Machine Learning, Vol. 2, No. 1. (January 2009), pp. 1-127, doi:10.1561/2200000006 by Y. Bengio posted to deep-learning machine-learning neural_network review by tomhebbron on 2012-06-25 20:03:36 along with 20 people Abstract
	Building high-level features using large scale unsupervised learning In International Conference in Machine Learning (2012) by Quoc Le, Marc'Aurelio Ranzato, Rajat Monga, et al. posted to deep-learning machine-learning unsupervised-learning by tomhebbron on 2012-06-23 13:55:28
	✔ Deep Convolutional Networks for Scene Parsing by David Grangier, Léon Bottou, Ronan Collobert posted to convnet deep-learning scene-parsing by assad79 on 2012-05-11 12:32:03 Abstract
	Understanding the difficulty of training deep feedforward neural networks In Proceedings of AISTATS 2010, Vol. 9 (May 2010), pp. 249-256 by Yoshua Bengio, Xavier Glorot posted to bengio deep-learning by lmsasu on 2012-02-11 09:32:56 along with 1 person Abstract
	Deep learning via semi-supervised embedding In Proceedings of the 25th Annual International Conference on Machine Learning (ICML 2008) (2008), pp. 1168-1175 by J. Weston, F. Ratle, R. Collobert edited by Andrew Mccallum, Sam Roweis posted to bib deep-learning ssl by abgoldberg on 2009-02-05 16:08:02 along with 1 person
	Semi-supervised learning of compact document representations with deep networks In Proceedings of the 25th Annual International Conference on Machine Learning (ICML 2008) (2008), pp. 792-799 by M. Ranzato, M. Szummer edited by Andrew Mccallum, Sam Roweis posted to bib deep-learning nlp ssl by abgoldberg on 2009-02-05 16:08:02

from:

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933 by Vincent Michalski, Roland Memisevic, Kishore Konda edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43
	✔ Unsupervised Learning of Video Representations using LSTMs (31 Mar 2015) by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54 along with 4 people Abstract
	✔ Better Computer Go Player with Neural Network and Long-term Prediction (26 Jan 2016) by Yuandong Tian, Yan Zhu posted to deep-learning games go by lehalle on 2015-12-09 17:57:52 along with 2 people Abstract
	✔ Fully Convolutional Networks for Semantic Segmentation (8 Mar 2015) by Jonathan Long, Evan Shelhamer, Trevor Darrell posted to deep-learning by hans_meine on 2015-12-04 19:12:45 along with 2 people Abstract Notes
	✔ Gradient Estimation Using Stochastic Computation Graphs (13 Nov 2015) by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 Abstract
	✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling (23 Sep 2015) by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 Abstract
	✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images (20 Nov 2015) by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21 along with 1 person Abstract
	✔ Variational Gaussian Process (20 Nov 2015) by Dustin Tran, Rajesh Ranganath, David M. Blei posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08 along with 1 person Abstract
	✔ SparkNet: Training Deep Networks in Spark (26 Nov 2015) by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30 along with 3 people Abstract
	✔ Deep Kalman Filters (16 Nov 2015) by Rahul G. Krishnan, Uri Shalit, David Sontag posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 Abstract
	✔ Sequence to Sequence Learning with Neural Networks (14 Dec 2014) by Ilya Sutskever, Oriol Vinyals, Quoc V. Le posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05 along with 4 people Abstract
	✔ Privacy-Preserving Deep Learning In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687 by Reza Shokri, Vitaly Shmatikov posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 Abstract
	✔ Predicting effects of noncoding variants with deep learning–based sequence model Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547 by Jian Zhou, Olga G. Troyanskaya posted to deep-learning functional-annotation non-coding by pickw on 2015-10-14 19:08:24 along with 8 people and 1 group
	✔ Curriculum Learning In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380 by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12 along with 2 people Abstract
	✔ High-order neural networks and kernel methods for peptide-MHC binding prediction Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371 by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein posted to deep-learning interaction machine-learning protein-protein by ajs625 on 2015-09-22 05:37:13 along with 1 person and 1 group Abstract
	✔ Deep Broad Learning - Big Models for Big Data (4 Sep 2015) by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 Abstract
	✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838 by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03 along with 1 person Abstract
	✔ A Neural Algorithm of Artistic Style (2 Sep 2015) by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59 along with 5 people Abstract
	✔ Quantum Deep Learning (22 May 2015) by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45 along with 2 people Abstract
	✔ Deep Learning for Single-View Instance Recognition (29 Jul 2015) by David Held, Sebastian Thrun, Silvio Savarese posted to deep-learning by noud88 on 2015-07-31 13:49:47 Abstract
	✔ Training Very Deep Networks (22 Jul 2015) by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber posted to deep-learning by mathkann on 2015-07-23 09:30:53 Abstract
	✔ Unsupervised Learning on Neural Network Outputs (7 Jul 2015) by Yao Lu posted to deep-learning by mathkann on 2015-07-08 14:23:44 Abstract
	✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding (29 May 2015) by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu posted to deep-learning by hukkinen on 2015-06-16 16:12:14 Abstract
	✔ Variational Inference with Normalizing Flows In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538 by Danilo J. Rezende, Shakir Mohamed posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 Abstract
	✔ Visualizing and Understanding Recurrent Networks (17 Nov 2015) by Andrej Karpathy, Justin Johnson, Li Fei-Fei posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34 along with 2 people Abstract
	✔ A Critical Review of Recurrent Neural Networks for Sequence Learning (29 Jun 2015) by Zachary C. Lipton posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02 along with 3 people Abstract
	✔ Blocks and Fuel: Frameworks for deep learning (1 Jun 2015) by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al. posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 Abstract
	Deep AutoRegressive Networks In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250 by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra edited by Tony Jebara, Eric P. Xing posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 Abstract
	✔ Building high-level features using large scale unsupervised learning In In International Conference on Machine Learning, 2012. 103 by Quoc V. Le, Rajat Monga, Matthieu Devin, et al. posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 Abstract
	✔ Reducing the dimensionality of data with neural networks. Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647 by G. E. Hinton, R. R. Salakhutdinov posted to deep-learning machine-learning print by falex on 2015-05-12 10:18:44 along with 50 people and 10 groups Abstract
	✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification (6 Feb 2015) by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun posted to deep-learning by mathkann on 2015-05-06 05:03:15 along with 3 people and 1 group Abstract
	✔ Low precision storage for deep learning (3 Apr 2015) by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David posted to deep-learning by mathkann on 2015-04-29 19:36:28 along with 1 person Abstract
	✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik posted to deep-learning by babakap on 2015-04-16 20:09:14 Abstract
	Theano: a CPU and GPU Math Expression Compiler In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010) by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al. posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58 along with 1 person Abstract
	✔ Theano: new features and speed improvements (23 Nov 2012) by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al. posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34 along with 3 people Abstract
	✔ Generative models for discovering sparse distributed representations Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101 by Geoffrey E. Hinton, Zoubin Ghahramani posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19 along with 4 people Abstract
	✔ On the Computational Efficiency of Training Neural Networks (28 Oct 2014) by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36 along with 3 people Abstract
	✔ Reweighted Wake-Sleep (11 Jun 2014) by Jörg Bornschein, Yoshua Bengio posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07 along with 1 person Abstract
	✔ Learning Stochastic Recurrent Networks (5 Mar 2015) by Justin Bayer, Christian Osendorfer posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42 along with 3 people Abstract
	✔ Towards Biologically Plausible Deep Learning (14 Feb 2015) by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15 along with 2 people Abstract
	✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years (31 Aug 2007) by Juergen Schmidhuber posted to agi deep-learning by chadwcarlson on 2015-04-12 11:17:52 along with 5 people and 1 group Abstract
	✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity (5 Sep 2007) by Juergen Schmidhuber posted to deep-learning machine-learning by chadwcarlson on 2015-04-12 11:17:21 along with 5 people and 2 groups Abstract
	✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3 by Tom Schaul, Leo Pape, Tobias Glasmachers, et al. edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40 along with 1 person Abstract
	✔ Visualizing and Understanding Convolutional Networks (28 Nov 2013) by Matthew D. Zeiler, Rob Fergus posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group Abstract
	✔ Greedy layer-wise training of deep networks In In NIPS (2007) by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, UniversitÃ© De MontrÃ©al, MontrÃ©al QuÃ©bec posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54 along with 10 people Abstract
	✔ Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53 along with 9 people and 1 group Abstract
	✔ Deep learning from temporal coherence in video In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469 by Hossein Mobahi, Ronan Collobert, Jason Weston posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35 along with 5 people Abstract
	✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units (7 Apr 2015) by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47 along with 1 person Abstract
	✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease. Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806 by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al. posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw on 2015-04-08 03:47:39 along with 22 people and 3 groups Abstract
	✔ Computational intelligence techniques in bioinformatics. Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47 by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 Abstract

http://www.citeulike.org/tag/deep-learning/page/1

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells"" In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933 by Vincent Michalski, Roland Memisevic, Kishore Konda edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43
	✔ Unsupervised Learning of Video Representations using LSTMs (31 Mar 2015) by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54 along with 4 people Abstract
	✔ Better Computer Go Player with Neural Network and Long-term Prediction (26 Jan 2016) by Yuandong Tian, Yan Zhu posted to deep-learning games go by lehalle on 2015-12-09 17:57:52 along with 2 people Abstract
	✔ Fully Convolutional Networks for Semantic Segmentation (8 Mar 2015) by Jonathan Long, Evan Shelhamer, Trevor Darrell posted to deep-learning by hans_meine on 2015-12-04 19:12:45 along with 2 people Abstract Notes
	✔ Gradient Estimation Using Stochastic Computation Graphs (13 Nov 2015) by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 Abstract
	✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling (23 Sep 2015) by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 Abstract
	✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images (20 Nov 2015) by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21 along with 1 person Abstract
	✔ Variational Gaussian Process (20 Nov 2015) by Dustin Tran, Rajesh Ranganath, David M. Blei posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08 along with 1 person Abstract
	✔ SparkNet: Training Deep Networks in Spark (26 Nov 2015) by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30 along with 3 people Abstract
	✔ Deep Kalman Filters (16 Nov 2015) by Rahul G. Krishnan, Uri Shalit, David Sontag posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 Abstract
	✔ Sequence to Sequence Learning with Neural Networks (14 Dec 2014) by Ilya Sutskever, Oriol Vinyals, Quoc V. Le posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05 along with 4 people Abstract
	✔ Privacy-Preserving Deep Learning In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687 by Reza Shokri, Vitaly Shmatikov posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 Abstract
	✔ Predicting effects of noncoding variants with deep learning–based sequence model Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547 by Jian Zhou, Olga G. Troyanskaya posted to deep-learning functional-annotation non-coding by pickw on 2015-10-14 19:08:24 along with 8 people and 1 group
	✔ Curriculum Learning In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380 by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12 along with 2 people Abstract
	✔ High-order neural networks and kernel methods for peptide-MHC binding prediction Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371 by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein posted to deep-learning interaction machine-learning protein-protein by ajs625 on 2015-09-22 05:37:13 along with 1 person and 1 group Abstract
	✔ Deep Broad Learning - Big Models for Big Data (4 Sep 2015) by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 Abstract
	✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838 by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03 along with 1 person Abstract
	✔ A Neural Algorithm of Artistic Style (2 Sep 2015) by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59 along with 5 people Abstract
	✔ Quantum Deep Learning (22 May 2015) by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45 along with 2 people Abstract
	✔ Deep Learning for Single-View Instance Recognition (29 Jul 2015) by David Held, Sebastian Thrun, Silvio Savarese posted to deep-learning by noud88 on 2015-07-31 13:49:47 Abstract
	✔ Training Very Deep Networks (22 Jul 2015) by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber posted to deep-learning by mathkann on 2015-07-23 09:30:53 Abstract
	✔ Unsupervised Learning on Neural Network Outputs (7 Jul 2015) by Yao Lu posted to deep-learning by mathkann on 2015-07-08 14:23:44 Abstract
	✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding (29 May 2015) by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu posted to deep-learning by hukkinen on 2015-06-16 16:12:14 Abstract
	✔ Variational Inference with Normalizing Flows In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538 by Danilo J. Rezende, Shakir Mohamed posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 Abstract
	✔ Visualizing and Understanding Recurrent Networks (17 Nov 2015) by Andrej Karpathy, Justin Johnson, Li Fei-Fei posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34 along with 2 people Abstract
	✔ A Critical Review of Recurrent Neural Networks for Sequence Learning (29 Jun 2015) by Zachary C. Lipton posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02 along with 3 people Abstract
	✔ Blocks and Fuel: Frameworks for deep learning (1 Jun 2015) by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al. posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 Abstract
	Deep AutoRegressive Networks In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250 by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra edited by Tony Jebara, Eric P. Xing posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 Abstract
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	Theano: a CPU and GPU Math Expression Compiler In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010) by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al. posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58 along with 1 person Abstract
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