Çaglar Gülçehre

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 66

Top Topics

Recurrent Neural Networks

Stochastic Gradient

Reinforcement Learning

Policy Evaluation

Top Venues

Publications

Chang Chen, Fei Deng, Kenji Kawaguchi, Çaglar Gülçehre, Sungjin Ahn
Simple Hierarchical Planning with Diffusion. CoRR (2024)
Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De
Resurrecting Recurrent Neural Networks for Long Sequences. ICML (2023)
Yeongbin Kim, Gautam Singh, Junyeong Park, Çaglar Gülçehre, Sungjin Ahn
Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models. CoRR (2023)
Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR (2023)
Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De
Resurrecting Recurrent Neural Networks for Long Sequences. CoRR (2023)
Çaglar Gülçehre, Tom Le Paine, Srivatsan Srinivasan, Ksenia Konyushkova, Lotte Weerts, Abhishek Sharma, Aditya Siddhant, Alex Ahern, Miaosen Wang, Chenjie Gu, Wolfgang Macherey, Arnaud Doucet, Orhan Firat, Nando de Freitas
Reinforced Self-Training (ReST) for Language Modeling. CoRR (2023)
Antonio Orvieto, Soham De, Çaglar Gülçehre, Razvan Pascanu, Samuel L. Smith
On the Universality of Linear Recurrences Followed by Nonlinear Projections. CoRR (2023)
Yeongbin Kim, Gautam Singh, Junyeong Park, Çaglar Gülçehre, Sungjin Ahn
Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models. NeurIPS (2023)
Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. 23 (2022)
Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet
An empirical study of implicit regularization in deep offline RL. Trans. Mach. Learn. Res. 2022 (2022)
Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matt Hoffman, Razvan Pascanu, Arnaud Doucet
An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR (2022)
Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR (2021)
Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
Active Offline Policy Selection. NeurIPS (2021)
Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas
Active Offline Policy Selection. CoRR (2021)
Çaglar Gülçehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew W. Hoffman, Razvan Pascanu, Nando de Freitas
Regularized Behavior Value Estimation. CoRR (2021)
Çaglar Gülçehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. ICLR (2020)
Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS (2020)
Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas
Hyperparameter Selection for Offline Reinforcement Learning. CoRR (2020)
Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Çaglar Gülçehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott E. Reed
Offline Learning from Demonstrations and Unlabeled Experience. CoRR (2020)
Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas
RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR (2020)
Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
Critic Regularized Regression. NeurIPS (2020)
Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
Critic Regularized Regression. CoRR (2020)
Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alexander Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas
Acme: A Research Framework for Distributed Reinforcement Learning. CoRR (2020)
Levent Sagun, Çaglar Gülçehre, Adriana Romero, Negar Rostemzadeh, Stefano Sarao Mannelli
Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver. CoRR (2020)
Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell
Stabilizing Transformers for Reinforcement Learning. ICML (2020)
Albert Gu, Çaglar Gülçehre, Thomas Paine, Matt Hoffman, Razvan Pascanu
Improving the Gating Mechanism of Recurrent Neural Networks. ICML (2020)
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. ICML (2019)
Albert Gu, Çaglar Gülçehre, Tom Le Paine, Matthew W. Hoffman, Razvan Pascanu
Improving the Gating Mechanism of Recurrent Neural Networks. CoRR (2019)
Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. 31 (4) (2019)
Tom Le Paine, Çaglar Gülçehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. CoRR (2019)
Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Çaglar Gülçehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas
Sample Efficient Adaptive Text-to-Speech. ICLR (Poster) (2019)
Çaglar Gülçehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter W. Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas
Hyperbolic Attention Networks. ICLR (Poster) (2019)
Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575 (7782) (2019)
Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell
Stabilizing Transformers for Reinforcement Learning. CoRR (2019)
Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
Gated Orthogonal Recurrent Units: On Learning to Forget. AAAI Workshops (2018)
Yutian Chen, Yannis M. Assael, Brendan Shillingford, David Budden, Scott E. Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Çaglar Gülçehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas
Sample Efficient Adaptive Text-to-Speech. CoRR (2018)
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu
Relational inductive biases, deep learning, and graph networks. CoRR (2018)
Çaglar Gülçehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter W. Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas
Hyperbolic Attention Networks. CoRR (2018)
Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio
Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. Neural Comput. 30 (4) (2018)
Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR (2018)
Çaglar Gülçehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Yoshua Bengio
On integrating a language model into neural machine translation. Comput. Speech Lang. 45 (2017)
Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio
Gated Orthogonal Recurrent Units: On Learning to Forget. CoRR (2017)
Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio
Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder. CoRR (2017)
Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models. NIPS (2017)
Xingdi Yuan, Tong Wang, Çaglar Gülçehre, Alessandro Sordoni, Philip Bachman, Sandeep Subramanian, Saizheng Zhang, Adam Trischler
Machine Comprehension by Text-to-Text Neural Question Generation. CoRR (2017)
Xingdi Yuan, Tong Wang, Çaglar Gülçehre, Alessandro Sordoni, Philip Bachman, Saizheng Zhang, Sandeep Subramanian, Adam Trischler
Machine Comprehension by Text-to-Text Neural Question Generation. Rep4NLP@ACL (2017)
Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio
Mollifying Networks. ICLR (Poster) (2017)
Francis Dutil, Çaglar Gülçehre, Adam Trischler, Yoshua Bengio
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models. CoRR (2017)
Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville
Recurrent Batch Normalization. ICLR (Poster) (2017)
Çaglar Gülçehre, Jose Sotelo, Marcin Moczulski, Yoshua Bengio
A Robust Adaptive Stochastic Gradient Method for Deep Learning. CoRR (2017)
Çaglar Gülçehre, Sarath Chandar, Yoshua Bengio
Memory Augmented Neural Networks with Wormhole Connections. CoRR (2017)
Çaglar Gülçehre, Jose Sotelo, Marcin Moczulski, Yoshua Bengio
A robust adaptive stochastic gradient method for deep learning. IJCNN (2017)
Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio
Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning. Rep4NLP@ACL (2017)
Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell
Policy Distillation. ICLR (Poster) (2016)
Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio
Mollifying Networks. CoRR (2016)
Ramesh Nallapati, Bowen Zhou, Cícero Nogueira dos Santos, Çaglar Gülçehre, Bing Xiang
Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond. CoNLL (2016)
Iulian Vlad Serban, Alberto García-Durán, Çaglar Gülçehre, Sungjin Ahn, Sarath Chandar, Aaron C. Courville, Yoshua Bengio
Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. CoRR (2016)
Çaglar Gülçehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua Bengio
Pointing the Unknown Words. CoRR (2016)
Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio
Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes. CoRR (2016)
Çaglar Gülçehre, Marcin Moczulski, Misha Denil, Yoshua Bengio
Noisy Activation Functions. ICML (2016)
Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
Çaglar Gülçehre, Marcin Moczulski, Misha Denil, Yoshua Bengio
Noisy Activation Functions. CoRR (2016)
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, Yoshua Bengio
EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10 (2) (2016)
Çaglar Gülçehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua Bengio
Pointing the Unknown Words. ACL (1) (2016)
Iulian Vlad Serban, Alberto García-Durán, Çaglar Gülçehre, Sungjin Ahn, Sarath Chandar, Aaron C. Courville, Yoshua Bengio
Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus. ACL (1) (2016)
Çaglar Gülçehre, Yoshua Bengio
Knowledge Matters: Importance of Prior Information for Optimization. J. Mach. Learn. Res. 17 (2016)
Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio
Gated Feedback Recurrent Neural Networks. CoRR (2015)
Çaglar Gülçehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Loïc Barrault, Huei-Chi Lin, Fethi Bougares, Holger Schwenk, Yoshua Bengio
On Using Monolingual Corpora in Neural Machine Translation. CoRR (2015)
Junyoung Chung, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio
Gated Feedback Recurrent Neural Networks. ICML (2015)
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Reddy Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher J. Pal, Yoshua Bengio
EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR (2015)
Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio
How to Construct Deep Recurrent Neural Networks. ICLR (Poster) (2014)
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Fethi Bougares, Holger Schwenk, Yoshua Bengio
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. CoRR (2014)
Çaglar Gülçehre, Yoshua Bengio
ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient. CoRR (2014)
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. EMNLP (2014)
Çaglar Gülçehre, KyungHyun Cho, Razvan Pascanu, Yoshua Bengio
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks. ECML/PKDD (1) (2014)
Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, KyungHyun Cho, Surya Ganguli, Yoshua Bengio
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. NIPS (2014)
Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. CoRR (2014)
Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. CoRR (2014)
Çaglar Gülçehre, Yoshua Bengio
Knowledge Matters: Importance of Prior Information for Optimization ICLR (2013)
Çaglar Gülçehre, Kyunghyun Cho, Razvan Pascanu, Yoshua Bengio
Learned-norm pooling for deep neural networks. CoRR (2013)
Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre, Roland Memisevic, Pascal Vincent, Aaron C. Courville, Yoshua Bengio, Raul Chandias Ferrari, Mehdi Mirza, Sébastien Jean, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu
Combining modality specific deep neural networks for emotion recognition in video. ICMI (2013)