Çaglar Gülçehre

According to our database, Çaglar Gülçehre authored at least 59 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.

Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Çaglar Gülçehre

CoRR, 2024

Simple Hierarchical Planning with Diffusion.

Chang Chen, Fei Deng, Kenji Kawaguchi, Çaglar Gülçehre, Sungjin Ahn

CoRR, 2024

2023

Reinforced Self-Training (ReST) for Language Modeling.

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

CoRR, 2023

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning.

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

CoRR, 2023

On the Universality of Linear Recurrences Followed by Nonlinear Projections.

Antonio Orvieto, Soham De, Çaglar Gülçehre, Razvan Pascanu, Samuel L. Smith

CoRR, 2023

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models.

Yeongbin Kim, Gautam Singh, Junyeong Park, Çaglar Gülçehre, Sungjin Ahn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Resurrecting Recurrent Neural Networks for Long Sequences.

Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De

Proceedings of the International Conference on Machine Learning, 2023

2022

An empirical study of implicit regularization in deep offline RL.

Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet

Trans. Mach. Learn. Res., 2022

On Instrumental Variable Regression for Deep Offline Policy Evaluation.

Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet

J. Mach. Learn. Res., 2022

2021

Regularized Behavior Value Estimation.

Çaglar Gülçehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew W. Hoffman, Razvan Pascanu, Nando de Freitas

CoRR, 2021

Active Offline Policy Selection.

Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Offline Learning from Demonstrations and Unlabeled Experience.

Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Çaglar Gülçehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott E. Reed

CoRR, 2020

Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver.

Levent Sagun, Çaglar Gülçehre, Adriana Romero, Negar Rostamzadeh, Stefano Sarao Mannelli

CoRR, 2020

Hyperparameter Selection for Offline Reinforcement Learning.

Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas

CoRR, 2020

RL Unplugged: Benchmarks for Offline Reinforcement Learning.

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

CoRR, 2020

Acme: A Research Framework for Distributed Reinforcement Learning.

Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal M. P. 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

CoRR, 2020

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Critic Regularized Regression.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Stabilizing Transformers for Reinforcement Learning.

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 M. Botvinick, Nicolas Heess, Raia Hadsell

Proceedings of the 37th International Conference on Machine Learning, 2020

Improving the Gating Mechanism of Recurrent Neural Networks.

Albert Gu, Çaglar Gülçehre, Thomas Paine, Matt Hoffman, Razvan Pascanu

Proceedings of the 37th International Conference on Machine Learning, 2020

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Gated Orthogonal Recurrent Units: On Learning to Forget.

Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio

Neural Comput., 2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

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

Nat., 2019

Improving the Gating Mechanism of Recurrent Neural Networks.

Albert Gu, Çaglar Gülçehre, Tom Le Paine, Matthew W. Hoffman, Razvan Pascanu

CoRR, 2019

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning.

Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

Proceedings of the 36th International Conference on Machine Learning, 2019

Hyperbolic Attention Networks.

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

Proceedings of the 7th International Conference on Learning Representations, 2019

Sample Efficient Adaptive Text-to-Speech.

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

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes.

Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio

Neural Comput., 2018

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL.

Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas

CoRR, 2018

Relational inductive biases, deep learning, and graph networks.

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 M. Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu

CoRR, 2018

2017

On integrating a language model into neural machine translation.

Çaglar Gülçehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Yoshua Bengio

Comput. Speech Lang., 2017

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder.

Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio

CoRR, 2017

Memory Augmented Neural Networks with Wormhole Connections.

Çaglar Gülçehre, Sarath Chandar, Yoshua Bengio

CoRR, 2017

Machine Comprehension by Text-to-Text Neural Question Generation.

Xingdi Yuan, Tong Wang, Çaglar Gülçehre, Alessandro Sordoni, Philip Bachman, Saizheng Zhang, Sandeep Subramanian, Adam Trischler

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning.

Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models.

Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A robust adaptive stochastic gradient method for deep learning.

Çaglar Gülçehre, Jose Sotelo, Marcin Moczulski, Yoshua Bengio

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Mollifying Networks.

Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio

Proceedings of the 5th International Conference on Learning Representations, 2017

Recurrent Batch Normalization.

Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

EmoNets: Multimodal deep learning approaches for emotion recognition in video.

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

J. Multimodal User Interfaces, 2016

Knowledge Matters: Importance of Prior Information for Optimization.

Çaglar Gülçehre, Yoshua Bengio

J. Mach. Learn. Res., 2016

Policy Distillation.

Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell

Proceedings of the 4th International Conference on Learning Representations, 2016

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes.

Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio

CoRR, 2016

Theano: A Python framework for fast computation of mathematical expressions.

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

CoRR, 2016

Noisy Activation Functions.

Çaglar Gülçehre, Marcin Moczulski, Misha Denil, Yoshua Bengio

Proceedings of the 33nd International Conference on Machine Learning, 2016

Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond.

Ramesh Nallapati, Bowen Zhou, Cícero Nogueira dos Santos, Çaglar Gülçehre, Bing Xiang

Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, 2016

Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus.

Iulian Vlad Serban, Alberto García-Durán, Çaglar Gülçehre, Sungjin Ahn, Sarath Chandar, Aaron C. Courville, Yoshua Bengio

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Pointing the Unknown Words.

Çaglar Gülçehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua Bengio

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015

On Using Monolingual Corpora in Neural Machine Translation.

Çaglar Gülçehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Loïc Barrault, Huei-Chi Lin, Fethi Bougares, Holger Schwenk, Yoshua Bengio

CoRR, 2015

Gated Feedback Recurrent Neural Networks.

Junyoung Chung, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

How to Construct Deep Recurrent Neural Networks.

Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio

Proceedings of the 2nd International Conference on Learning Representations, 2014

ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient.

Çaglar Gülçehre, Yoshua Bengio

CoRR, 2014

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio

CoRR, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Fethi Bougares, Holger Schwenk, Yoshua Bengio

CoRR, 2014

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks.

Çaglar Gülçehre, KyungHyun Cho, Razvan Pascanu, Yoshua Bengio

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Identifying and attacking the saddle point problem in high-dimensional non-convex optimization.

Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, KyungHyun Cho, Surya Ganguli, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2013

Learned-norm pooling for deep neural networks.

Çaglar Gülçehre, Kyunghyun Cho, Razvan Pascanu, Yoshua Bengio

CoRR, 2013

Combining modality specific deep neural networks for emotion recognition in video.

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

Proceedings of the 2013 International Conference on Multimodal Interaction, 2013