ICLR 2017

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iclr2016:accepted-main [2017/10/08 12:23]
rnogueira created
iclr2016:accepted-main [2017/10/08 12:37] (current)
rnogueira
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-==== Accepted Papers (Conference Track) ====+====== Accepted Papers (Conference Track) ​======
  
-  ​- [[http://​arxiv.org/​abs/​1511.07122|Multi-Scale Context Aggregation ​by Dilated Convolutions]]\\ Fisher Yu,  ​Vladlen Koltun+====Oral Presentations==== 
 + 
 + 
 +  ​- [[http://​arxiv.org/​abs/​1511.06279|Neural Programmer-Interpreters]]\\ Scott Reed,  Nando de Freitas 
 +  - [[http://​arxiv.org/​abs/​1511.08400|Regularizing RNNs by Stabilizing Activations]]\\ David Krueger, ​ Roland Memisevic 
 +  - [[http://​arxiv.org/​abs/​1511.06909|BlackOut:​ Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies]] [[https://​github.com/​IntelLabs/​rnnlm|[code]]]\\ Shihao Ji,  Swaminathan Vishwanathan, ​ Nadathur Satish, ​ Michael Anderson, ​ Pradeep Dubey 
 +  - [[http://​arxiv.org/​abs/​1511.02301|The Goldilocks Principle: Reading Children'​s Books with Explicit Memory Representations]]\\ Felix Hill,  Antoine Bordes, ​ Sumit Chopra, ​ Jason Weston 
 +  - [[http://​arxiv.org/​abs/​1511.08198|Towards Universal Paraphrastic Sentence Embeddings]] [[https://​github.com/​jwieting/​iclr2016|[code]]]\\ John Wieting, ​ Mohit Bansal, ​ Kevin Gimpel, ​ Karen Livescu 
 +  - [[http://​arxiv.org/​abs/​1511.07543|Convergent Learning: Do different neural networks learn the same representations?​]]\\ Yixuan Li,  Jason Yosinski, ​ Jeff Clune, ​ Hod Lipson, ​ John Hopcroft 
 +  - [[http://​arxiv.org/​abs/​1511.05641|Net2Net:​ Accelerating Learning via Knowledge Transfer]]\\ Tianqi Chen,  Ian Goodfellow, ​ Jon Shlens 
 +  - [[http://​arxiv.org/​abs/​1511.06499|Variational Gaussian Process]]\\ Dustin Tran,  Rajesh Ranganath,  ​David Blei
   - [[http://​arxiv.org/​abs/​1511.00830|The Variational Fair Autoencoder]]\\ Christos Louizos, ​ Kevin Swersky, ​ Yujia Li,  Max Welling, ​ Richard Zemel   - [[http://​arxiv.org/​abs/​1511.00830|The Variational Fair Autoencoder]]\\ Christos Louizos, ​ Kevin Swersky, ​ Yujia Li,  Max Welling, ​ Richard Zemel
   - [[http://​arxiv.org/​abs/​1511.01844|A note on the evaluation of generative models]]\\ Lucas Theis, ​ Aäron van den Oord,  Matthias Bethge   - [[http://​arxiv.org/​abs/​1511.01844|A note on the evaluation of generative models]]\\ Lucas Theis, ​ Aäron van den Oord,  Matthias Bethge
 +  - [[http://​arxiv.org/​abs/​1510.00149|Deep Compression:​ Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding]]\\ Song Han,  Huizi Mao,  Bill Dally
 +  - [[http://​arxiv.org/​abs/​1510.03009|Neural Networks with Few Multiplications]]\\ Zhouhan Lin,  Matthieu Courbariaux, ​ Roland Memisevic, ​ Yoshua Bengio
 +  - [[http://​arxiv.org/​abs/​1511.06361|Order-Embeddings of Images and Language]] [[https://​github.com/​ivendrov/​order-embedding|[code]]]\\ Ivan Vendrov, ​ Ryan Kiros, ​ Sanja Fidler, ​ Raquel Urtasun
 +  - [[http://​arxiv.org/​abs/​1511.02793|Generating Images from Captions with Attention]]\\ Elman Mansimov, ​ Emilio Parisotto, ​ Jimmy Ba,  Ruslan Salakhutdinov
 +  - [[http://​arxiv.org/​abs/​1511.06281|Density Modeling of Images using a Generalized Normalization Transformation]]\\ Johannes Ballé, ​ Valero Laparra, ​ Eero Simoncelli
 +
 +
 +
 +====Poster Presentations====
 +
 +
 +  - [[http://​arxiv.org/​abs/​1511.07122|Multi-Scale Context Aggregation by Dilated Convolutions]]\\ Fisher Yu,  Vladlen Koltun
   - [[http://​arxiv.org/​abs/​1511.03677|Learning to Diagnose with LSTM Recurrent Neural Networks]]\\ Zachary Lipton, ​ David Kale,  Charles Elkan, ​ Randall Wetzel   - [[http://​arxiv.org/​abs/​1511.03677|Learning to Diagnose with LSTM Recurrent Neural Networks]]\\ Zachary Lipton, ​ David Kale,  Charles Elkan, ​ Randall Wetzel
   - [[http://​arxiv.org/​abs/​1511.05952|Prioritized Experience Replay]]\\ Tom Schaul, ​ John Quan,  Ioannis Antonoglou, ​ David Silver   - [[http://​arxiv.org/​abs/​1511.05952|Prioritized Experience Replay]]\\ Tom Schaul, ​ John Quan,  Ioannis Antonoglou, ​ David Silver
   - [[http://​arxiv.org/​abs/​1509.00519|Importance Weighted Autoencoders]]\\ Yuri Burda, ​ Ruslan Salakhutdinov, ​ Roger Grosse   - [[http://​arxiv.org/​abs/​1509.00519|Importance Weighted Autoencoders]]\\ Yuri Burda, ​ Ruslan Salakhutdinov, ​ Roger Grosse
-  - [[http://​arxiv.org/​abs/​1510.00149|Deep Compression:​ Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding]]\\ Song Han,  Huizi Mao,  Bill Dally 
   - [[http://​arxiv.org/​abs/​1511.06455|Variationally Auto-Encoded Deep Gaussian Processes]]\\ Zhenwen Dai,  Andreas Damianou, ​ Javier Gonzalez, ​ Neil Lawrence   - [[http://​arxiv.org/​abs/​1511.06455|Variationally Auto-Encoded Deep Gaussian Processes]]\\ Zhenwen Dai,  Andreas Damianou, ​ Javier Gonzalez, ​ Neil Lawrence
   - [[http://​arxiv.org/​abs/​1511.06744|Training Convolutional Neural Networks with Low-rank Filters for Efficient Image Classification]]\\ Yani Ioannou, ​ Duncan Robertson, ​ Jamie Shotton, ​ roberto Cipolla, ​ Antonio Criminisi, ​ Jamie Shotton   - [[http://​arxiv.org/​abs/​1511.06744|Training Convolutional Neural Networks with Low-rank Filters for Efficient Image Classification]]\\ Yani Ioannou, ​ Duncan Robertson, ​ Jamie Shotton, ​ roberto Cipolla, ​ Antonio Criminisi, ​ Jamie Shotton
-  - [[http://​arxiv.org/​abs/​1510.03009|Neural Networks with Few Multiplications]]\\ Zhouhan Lin,  Matthieu Courbariaux, ​ Roland Memisevic, ​ Yoshua Bengio 
   - [[http://​arxiv.org/​abs/​1511.06068|Reducing Overfitting in Deep Networks by Decorrelating Representations]]\\ Michael Cogswell, ​ Faruk Ahmed, ​ Ross Girshick, ​ Larry Zitnick, ​ Dhruv Batra   - [[http://​arxiv.org/​abs/​1511.06068|Reducing Overfitting in Deep Networks by Decorrelating Representations]]\\ Michael Cogswell, ​ Faruk Ahmed, ​ Ross Girshick, ​ Larry Zitnick, ​ Dhruv Batra
   - [[http://​arxiv.org/​abs/​1511.07386|Pushing the Boundaries of Boundary Detection using Deep Learning]]\\ Iasonas Kokkinos   - [[http://​arxiv.org/​abs/​1511.07386|Pushing the Boundaries of Boundary Detection using Deep Learning]]\\ Iasonas Kokkinos
-  - [[http://​arxiv.org/​abs/​1511.02793|Generating Images from Captions with Attention]]\\ Elman Mansimov, ​ Emilio Parisotto, ​ Jimmy Ba,  Ruslan Salakhutdinov 
   - [[http://​arxiv.org/​abs/​1509.06664|Reasoning about Entailment with Neural Attention]]\\ Tim Rocktäschel, ​ Edward Grefenstette, ​ Karl Moritz Hermann, ​ Tomáš Kočiský, ​ Phil Blunsom   - [[http://​arxiv.org/​abs/​1509.06664|Reasoning about Entailment with Neural Attention]]\\ Tim Rocktäschel, ​ Edward Grefenstette, ​ Karl Moritz Hermann, ​ Tomáš Kočiský, ​ Phil Blunsom
   - [[http://​arxiv.org/​abs/​1511.06067|Convolutional Neural Networks With Low-rank Regularization]]\\ Cheng Tai,  Tong Xiao,  Yi Zhang, ​ Xiaogang Wang,  Weinan E   - [[http://​arxiv.org/​abs/​1511.06067|Convolutional Neural Networks With Low-rank Regularization]]\\ Cheng Tai,  Tong Xiao,  Yi Zhang, ​ Xiaogang Wang,  Weinan E
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   - [[http://​arxiv.org/​abs/​1506.05011|Bayesian Representation Learning with Oracle Constraints]]\\ Theofanis Karaletsos, ​ Serge Belongie, ​ Gunnar Rätsch   - [[http://​arxiv.org/​abs/​1506.05011|Bayesian Representation Learning with Oracle Constraints]]\\ Theofanis Karaletsos, ​ Serge Belongie, ​ Gunnar Rätsch
   - [[http://​arxiv.org/​abs/​1511.04834|Neural Programmer: Inducing Latent Programs with Gradient Descent]]\\ Arvind Neelakantan, ​ Quoc Le,  Ilya Sutskever   - [[http://​arxiv.org/​abs/​1511.04834|Neural Programmer: Inducing Latent Programs with Gradient Descent]]\\ Arvind Neelakantan, ​ Quoc Le,  Ilya Sutskever
-  - [[http://​arxiv.org/​abs/​1511.08198|Towards Universal Paraphrastic Sentence Embeddings]] [[https://​github.com/​jwieting/​iclr2016|[code]]]\\ John Wieting, ​ Mohit Bansal, ​ Kevin Gimpel, ​ Karen Livescu 
-  - [[http://​arxiv.org/​abs/​1511.08400|Regularizing RNNs by Stabilizing Activations]]\\ David Krueger, ​ Roland Memisevic 
   - [[http://​arxiv.org/​abs/​1511.06051|SparkNet:​ Training Deep Networks in Spark]]\\ Philipp Moritz, ​ Robert Nishihara, ​ Ion Stoica, ​ Michael Jordan   - [[http://​arxiv.org/​abs/​1511.06051|SparkNet:​ Training Deep Networks in Spark]]\\ Philipp Moritz, ​ Robert Nishihara, ​ Ion Stoica, ​ Michael Jordan
   - [[http://​arxiv.org/​abs/​1511.06390|Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks]]\\ Jost Tobias Springenberg   - [[http://​arxiv.org/​abs/​1511.06390|Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks]]\\ Jost Tobias Springenberg
-  - [[http://​arxiv.org/​abs/​1511.02301|The Goldilocks Principle: Reading Children'​s Books with Explicit Memory Representations]]\\ Felix Hill,  Antoine Bordes, ​ Sumit Chopra, ​ Jason Weston 
   - [[http://​arxiv.org/​abs/​1511.05176|MuProp:​ Unbiased Backpropagation For Stochastic Neural Networks]]\\ Shixiang Gu,  Sergey Levine, ​ Ilya Sutskever, ​ Andriy Mnih   - [[http://​arxiv.org/​abs/​1511.05176|MuProp:​ Unbiased Backpropagation For Stochastic Neural Networks]]\\ Shixiang Gu,  Sergey Levine, ​ Ilya Sutskever, ​ Andriy Mnih
   - [[http://​arxiv.org/​abs/​1511.06606|Data Representation and Compression Using Linear-Programming Approximations]]\\ Hristo Paskov, ​ John Mitchell, ​ Trevor Hastie   - [[http://​arxiv.org/​abs/​1511.06606|Data Representation and Compression Using Linear-Programming Approximations]]\\ Hristo Paskov, ​ John Mitchell, ​ Trevor Hastie
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   - [[http://​arxiv.org/​abs/​1511.04581|A Test of Relative Similarity for Model Selection in Generative Models]]\\ Eugene Belilovsky, ​ Wacha Bounliphone, ​ Matthew Blaschko, ​ Ioannis Antonoglou, ​ Arthur Gretton   - [[http://​arxiv.org/​abs/​1511.04581|A Test of Relative Similarity for Model Selection in Generative Models]]\\ Eugene Belilovsky, ​ Wacha Bounliphone, ​ Matthew Blaschko, ​ Ioannis Antonoglou, ​ Arthur Gretton
   - [[http://​arxiv.org/​abs/​1511.06530|Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications]]\\ Yong-Deok Kim,  Eunhyeok Park,  Sungjoo Yoo,  Taelim Choi,  Lu Yang,  Dongjun Shin   - [[http://​arxiv.org/​abs/​1511.06530|Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications]]\\ Yong-Deok Kim,  Eunhyeok Park,  Sungjoo Yoo,  Taelim Choi,  Lu Yang,  Dongjun Shin
-  - [[http://​arxiv.org/​abs/​1511.06279|Neural Programmer-Interpreters]]\\ Scott Reed,  Nando de Freitas 
   - [[http://​arxiv.org/​abs/​1511.06939|Session-based recommendations with recurrent neural networks]] [[https://​github.com/​hidasib/​GRU4Rec|[code]]]\\ Balázs Hidasi, ​ Alexandros Karatzoglou, ​ Linas Baltrunas, ​ Domonkos Tikk   - [[http://​arxiv.org/​abs/​1511.06939|Session-based recommendations with recurrent neural networks]] [[https://​github.com/​hidasib/​GRU4Rec|[code]]]\\ Balázs Hidasi, ​ Alexandros Karatzoglou, ​ Linas Baltrunas, ​ Domonkos Tikk
   - [[http://​arxiv.org/​abs/​1509.02971|Continuous control with deep reinforcement learning]]\\ Timothy Lillicrap, ​ Jonathan Hunt,  Alexander Pritzel, ​ Nicolas Heess, ​ Tom Erez,  Yuval Tassa, ​ David Silver, ​ Daan Wierstra   - [[http://​arxiv.org/​abs/​1509.02971|Continuous control with deep reinforcement learning]]\\ Timothy Lillicrap, ​ Jonathan Hunt,  Alexander Pritzel, ​ Nicolas Heess, ​ Tom Erez,  Yuval Tassa, ​ David Silver, ​ Daan Wierstra
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   - [[http://​arxiv.org/​abs/​1411.7676|Modeling Visual Representations:​Defining Properties and Deep Approximations]]\\ Stefano Soatto, ​ Alessandro Chiuso   - [[http://​arxiv.org/​abs/​1411.7676|Modeling Visual Representations:​Defining Properties and Deep Approximations]]\\ Stefano Soatto, ​ Alessandro Chiuso
   - [[http://​arxiv.org/​abs/​1511.07069|Auxiliary Image Regularization for Deep CNNs with Noisy Labels]]\\ Samaneh Azadi, ​ Jiashi Feng,  Stefanie Jegelka, ​ Trevor Darrell   - [[http://​arxiv.org/​abs/​1511.07069|Auxiliary Image Regularization for Deep CNNs with Noisy Labels]]\\ Samaneh Azadi, ​ Jiashi Feng,  Stefanie Jegelka, ​ Trevor Darrell
-  - [[http://​arxiv.org/​abs/​1511.07543|Convergent Learning: Do different neural networks learn the same representations?​]]\\ Yixuan Li,  Jason Yosinski, ​ Jeff Clune, ​ Hod Lipson, ​ John Hopcroft 
   - [[http://​arxiv.org/​abs/​1511.06295|Policy Distillation]]\\ Andrei Rusu,  Sergio Gomez, ​ Caglar Gulcehre, ​ Guillaume Desjardins, ​ James Kirkpatrick, ​ Razvan Pascanu, ​ Volodymyr Mnih,  Koray Kavukcuoglu, ​ Raia Hadsell   - [[http://​arxiv.org/​abs/​1511.06295|Policy Distillation]]\\ Andrei Rusu,  Sergio Gomez, ​ Caglar Gulcehre, ​ Guillaume Desjardins, ​ James Kirkpatrick, ​ Razvan Pascanu, ​ Volodymyr Mnih,  Koray Kavukcuoglu, ​ Raia Hadsell
   - [[http://​arxiv.org/​abs/​1511.06392|Neural Random-Access Machines]]\\ Karol Kurach, ​ Marcin Andrychowicz, ​ Ilya Sutskever   - [[http://​arxiv.org/​abs/​1511.06392|Neural Random-Access Machines]]\\ Karol Kurach, ​ Marcin Andrychowicz, ​ Ilya Sutskever
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   - [[http://​arxiv.org/​abs/​1511.05939|Metric Learning with Adaptive Density Discrimination]]\\ Oren Rippel, ​ Manohar Paluri, ​ Piotr Dollar, ​ Lubomir Bourdev   - [[http://​arxiv.org/​abs/​1511.05939|Metric Learning with Adaptive Density Discrimination]]\\ Oren Rippel, ​ Manohar Paluri, ​ Piotr Dollar, ​ Lubomir Bourdev
   - [[http://​arxiv.org/​abs/​1511.05897|Censoring Representations with an Adversary]]\\ Harrison Edwards, ​ Amos Storkey   - [[http://​arxiv.org/​abs/​1511.05897|Censoring Representations with an Adversary]]\\ Harrison Edwards, ​ Amos Storkey
-  - [[http://​arxiv.org/​abs/​1511.06361|Order-Embeddings of Images and Language]] [[https://​github.com/​ivendrov/​order-embedding|[code]]]\\ Ivan Vendrov, ​ Ryan Kiros, ​ Sanja Fidler, ​ Raquel Urtasun 
   - [[http://​arxiv.org/​abs/​1511.06085|Variable Rate Image Compression with Recurrent Neural Networks]]\\ George Toderici, ​ Sean O'​Malley, ​ Damien Vincent, ​ Sung Jin Hwang, ​ Michele Covell, ​ Shumeet Baluja, ​ Rahul Sukthankar, ​ David Minnen   - [[http://​arxiv.org/​abs/​1511.06085|Variable Rate Image Compression with Recurrent Neural Networks]]\\ George Toderici, ​ Sean O'​Malley, ​ Damien Vincent, ​ Sung Jin Hwang, ​ Michele Covell, ​ Shumeet Baluja, ​ Rahul Sukthankar, ​ David Minnen
   - [[http://​arxiv.org/​abs/​1511.06432|Delving Deeper into Convolutional Networks for Learning Video Representations]]\\ Nicolas Ballas, ​ Li Yao,  Pal Chris, ​ Aaron Courville   - [[http://​arxiv.org/​abs/​1511.06432|Delving Deeper into Convolutional Networks for Learning Video Representations]]\\ Nicolas Ballas, ​ Li Yao,  Pal Chris, ​ Aaron Courville
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   - [[http://​arxiv.org/​abs/​1511.06391|Order Matters: Sequence to sequence for sets]]\\ Oriol Vinyals, ​ Samy Bengio, ​ Manjunath Kudlur   - [[http://​arxiv.org/​abs/​1511.06391|Order Matters: Sequence to sequence for sets]]\\ Oriol Vinyals, ​ Samy Bengio, ​ Manjunath Kudlur
   - [[http://​arxiv.org/​abs/​1506.02438|High-Dimensional Continuous Control Using Generalized Advantage Estimation]]\\ John Schulman, ​ Philipp Moritz, ​ Sergey Levine, ​ Michael Jordan, ​ Pieter Abbeel   - [[http://​arxiv.org/​abs/​1506.02438|High-Dimensional Continuous Control Using Generalized Advantage Estimation]]\\ John Schulman, ​ Philipp Moritz, ​ Sergey Levine, ​ Michael Jordan, ​ Pieter Abbeel
-  - [[http://​arxiv.org/​abs/​1511.06909|BlackOut:​ Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies]] [[https://​github.com/​IntelLabs/​rnnlm|[code]]]\\ Shihao Ji,  Swaminathan Vishwanathan, ​ Nadathur Satish, ​ Michael Anderson, ​ Pradeep Dubey 
   - [[http://​arxiv.org/​abs/​1511.05440|Deep Multi Scale Video Prediction Beyond Mean Square Error]]\\ Michael Mathieu, ​ camille couprie, ​ Yann Lecun   - [[http://​arxiv.org/​abs/​1511.05440|Deep Multi Scale Video Prediction Beyond Mean Square Error]]\\ Michael Mathieu, ​ camille couprie, ​ Yann Lecun
   - [[http://​arxiv.org/​abs/​1507.01526|Grid Long Short-Term Memory]]\\ Nal Kalchbrenner, ​ Alex Graves, ​ Ivo Danihelka   - [[http://​arxiv.org/​abs/​1507.01526|Grid Long Short-Term Memory]]\\ Nal Kalchbrenner, ​ Alex Graves, ​ Ivo Danihelka
-  - [[http://​arxiv.org/​abs/​1511.05641|Net2Net:​ Accelerating Learning via Knowledge Transfer]]\\ Tianqi Chen,  Ian Goodfellow, ​ Jon Shlens 
   - [[http://​arxiv.org/​abs/​1511.05622|Predicting distributions with Linearizing Belief Networks]]\\ Yann Dauphin, ​ David Grangier   - [[http://​arxiv.org/​abs/​1511.05622|Predicting distributions with Linearizing Belief Networks]]\\ Yann Dauphin, ​ David Grangier
   - [[http://​arxiv.org/​abs/​1511.07289|Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)]]\\ Djork-Arné ​ Clevert, ​ Thomas Unterthiner, ​ Sepp Hochreiter   - [[http://​arxiv.org/​abs/​1511.07289|Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)]]\\ Djork-Arné ​ Clevert, ​ Thomas Unterthiner, ​ Sepp Hochreiter
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   - [[http://​arxiv.org/​abs/​1511.08228|Neural GPUs Learn Algorithms]] [[https://​github.com/​tensorflow/​models/​tree/​master/​neural_gpu|[code]]] [[https://​www.youtube.com/​watch?​v=LzC8NkTZAF4|[video]]]\\ Lukasz Kaiser, ​ Ilya Sutskever   - [[http://​arxiv.org/​abs/​1511.08228|Neural GPUs Learn Algorithms]] [[https://​github.com/​tensorflow/​models/​tree/​master/​neural_gpu|[code]]] [[https://​www.youtube.com/​watch?​v=LzC8NkTZAF4|[video]]]\\ Lukasz Kaiser, ​ Ilya Sutskever
   - [[http://​arxiv.org/​abs/​1511.05946|ACDC:​ A Structured Efficient Linear Layer ]]\\ Marcin Moczulski, ​ Misha Denil, ​ Jeremy Appleyard, ​ Nando de Freitas   - [[http://​arxiv.org/​abs/​1511.05946|ACDC:​ A Structured Efficient Linear Layer ]]\\ Marcin Moczulski, ​ Misha Denil, ​ Jeremy Appleyard, ​ Nando de Freitas
-  - [[http://​arxiv.org/​abs/​1511.06281|Density Modeling of Images using a Generalized Normalization Transformation]]\\ Johannes Ballé, ​ Valero Laparra, ​ Eero Simoncelli 
   - [[http://​arxiv.org/​abs/​1511.05122|Adversarial Manipulation of Deep Representations]] [[https://​github.com/​fartashf/​under_convnet|[code]]]\\ Sara Sabour, ​ Yanshuai Cao,  Fartash Faghri, ​ David Fleet   - [[http://​arxiv.org/​abs/​1511.05122|Adversarial Manipulation of Deep Representations]] [[https://​github.com/​fartashf/​under_convnet|[code]]]\\ Sara Sabour, ​ Yanshuai Cao,  Fartash Faghri, ​ David Fleet
   - [[http://​arxiv.org/​abs/​1511.06394|Geodesics of learned representations]]\\ Olivier Hénaff, ​ Eero Simoncelli   - [[http://​arxiv.org/​abs/​1511.06394|Geodesics of learned representations]]\\ Olivier Hénaff, ​ Eero Simoncelli
   - [[http://​arxiv.org/​abs/​1511.06732|Sequence Level Training with Recurrent Neural Networks]]\\ Marc'​Aurelio Ranzato, ​ Sumit Chopra, ​ Michael Auli,  Wojciech Zaremba   - [[http://​arxiv.org/​abs/​1511.06732|Sequence Level Training with Recurrent Neural Networks]]\\ Marc'​Aurelio Ranzato, ​ Sumit Chopra, ​ Michael Auli,  Wojciech Zaremba
   - [[http://​arxiv.org/​abs/​1511.05666|Super-resolution with deep convolutional sufficient statistics]]\\ Joan Bruna, ​ Pablo Sprechmann, ​ Yann Lecun   - [[http://​arxiv.org/​abs/​1511.05666|Super-resolution with deep convolutional sufficient statistics]]\\ Joan Bruna, ​ Pablo Sprechmann, ​ Yann Lecun
-  - [[http://​arxiv.org/​abs/​1511.06499|Variational Gaussian Process]]\\ Dustin Tran,  Rajesh Ranganath, ​ David Blei 
  
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