Tag deep-learning 一大堆深度学习论文
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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ Greedy layer-wise training of deep networks
In In NIPS (2007)
by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec
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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ Greedy layer-wise training of deep networks
In In NIPS (2007)
by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec
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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ Greedy layer-wise training of deep networks
In In NIPS (2007)
by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec
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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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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
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✔ 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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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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
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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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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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
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✔ 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
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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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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✔ 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
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