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Caglar Gulcehre
Çaglar Gülçehre
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2020 – today
- 2024
- [c35]Dominik Stammbach, Philine Widmer, Eunjung Cho, Caglar Gulcehre, Elliott Ash:
Aligning Large Language Models with Diverse Political Viewpoints. EMNLP 2024: 7257-7267 - [c34]Tim R. Davidson, Viacheslav Surkov, Veniamin Veselovsky, Giuseppe Russo Latona, Robert West, Caglar Gulcehre:
Self-Recognition in Language Models. EMNLP (Findings) 2024: 12032-12059 - [c33]Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
Simple Hierarchical Planning with Diffusion. ICLR 2024 - [c32]Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. ICML 2024 - [c31]Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu, Samuel L. Smith:
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues. ICML 2024 - [i55]Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre
, Sungjin Ahn:
Simple Hierarchical Planning with Diffusion. CoRR abs/2401.02644 (2024) - [i54]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, Caglar Gulcehre
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR abs/2402.19427 (2024) - [i53]Skander Moalla, Andrea Miele, Razvan Pascanu, Caglar Gulcehre:
No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO. CoRR abs/2405.00662 (2024) - [i52]Akhil Arora, Lars Henning Klein, Nearchos Potamitis, Roland Aydin, Caglar Gulcehre, Robert West:
Fleet of Agents: Coordinated Problem Solving with Large Language Models using Genetic Particle Filtering. CoRR abs/2405.06691 (2024) - [i51]Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. CoRR abs/2406.06793 (2024) - [i50]Justin Deschenaux, Caglar Gulcehre:
Promises, Outlooks and Challenges of Diffusion Language Modeling. CoRR abs/2406.11473 (2024) - [i49]Dominik Stammbach, Philine Widmer, Eunjung Cho, Caglar Gulcehre, Elliott Ash:
Aligning Large Language Models with Diverse Political Viewpoints. CoRR abs/2406.14155 (2024) - [i48]Xiuying Wei, Skander Moalla, Razvan Pascanu, Caglar Gulcehre:
Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers. CoRR abs/2406.16450 (2024) - [i47]Tim R. Davidson, Viacheslav Surkov, Veniamin Veselovsky, Giuseppe Russo Latona, Robert West, Caglar Gulcehre:
Self-Recognition in Language Models. CoRR abs/2407.06946 (2024) - [i46]Federico Arangath Joseph, Kilian Konstantin Haefeli, Noah Liniger, Caglar Gulcehre:
HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context. CoRR abs/2407.09375 (2024) - [i45]Xiuying Wei, Skander Moalla, Razvan Pascanu, Caglar Gulcehre:
Investigating Low-Rank Training in Transformer Language Models: Efficiency and Scaling Analysis. CoRR abs/2407.09835 (2024) - [i44]Mikhail Terekhov, Caglar Gulcehre:
In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning. CoRR abs/2407.16807 (2024) - [i43]Denis Tarasov, Anja Surina, Caglar Gulcehre:
The Role of Deep Learning Regularizations on Actors in Offline RL. CoRR abs/2409.07606 (2024) - 2023
- [c30]Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De:
Resurrecting Recurrent Neural Networks for Long Sequences. ICML 2023: 26670-26698 - [c29]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 - [i42]Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre
Resurrecting Recurrent Neural Networks for Long Sequences. CoRR abs/2303.06349 (2023) - [i41]Antonio Orvieto, Soham De, Çaglar Gülçehre, Razvan Pascanu, Samuel L. Smith:
On the Universality of Linear Recurrences Followed by Nonlinear Projections. CoRR abs/2307.11888 (2023) - [i40]Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR abs/2308.03526 (2023) - [i39]Çaglar Gülçehre
Reinforced Self-Training (ReST) for Language Modeling. CoRR abs/2308.08998 (2023) - [i38]Yeongbin Kim, Gautam Singh, Junyeong Park, Çaglar Gülçehre
Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models. CoRR abs/2311.09064 (2023) - 2022
- [j8]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: 302:1-302:40 (2022) - [j7]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) - [i37]Çaglar Gülçehre
An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR abs/2207.02099 (2022) - 2021
- [c28]Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. NeurIPS 2021: 24631-24644 - [i36]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 abs/2103.09575 (2021) - [i35]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 abs/2105.10148 (2021) - [i34]Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. CoRR abs/2106.10251 (2021) - 2020
- [c27]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 - [c26]Albert Gu, Çaglar Gülçehre, Thomas Paine, Matt Hoffman, Razvan Pascanu:
Improving the Gating Mechanism of Recurrent Neural Networks. ICML 2020: 3800-3809 - [c25]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:
Stabilizing Transformers for Reinforcement Learning. ICML 2020: 7487-7498 - [c24]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 - [c23]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 - [i33]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:
Acme: A Research Framework for Distributed Reinforcement Learning. CoRR abs/2006.00979 (2020) - [i32]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 abs/2006.13888 (2020) - [i31]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 abs/2006.15134 (2020) - [i30]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 abs/2007.09055 (2020) - [i29]Levent Sagun, Çaglar Gülçehre, Adriana Romero, Negar Rostamzadeh, Stefano Sarao Mannelli:
Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver. CoRR abs/2007.13483 (2020) - [i28]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 abs/2011.13885 (2020)
2010 – 2019
- 2019
- [j6]Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575(7782): 350-354 (2019) - [j5]Li Jing, Çaglar Gülçehre
Gated Orthogonal Recurrent Units: On Learning to Forget. Neural Comput. 31(4) (2019) - [c22]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 - [c21]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 - [c20]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: 3040-3049 - [i27]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 abs/1909.01387 (2019) - [i26]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 abs/1910.06764 (2019) - [i25]Albert Gu, Çaglar Gülçehre, Tom Le Paine, Matthew W. Hoffman, Razvan Pascanu:
Improving the Gating Mechanism of Recurrent Neural Networks. CoRR abs/1910.09890 (2019) - 2018
- [j4]Çaglar Gülçehre
Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. Neural Comput. 30(4) (2018) - [c19]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: 720-726 - [i24]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 abs/1805.09786 (2018) - [i23]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:
Relational inductive biases, deep learning, and graph networks. CoRR abs/1806.01261 (2018) - [i22]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 abs/1809.10460 (2018) - [i21]Natasha Jaques
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR abs/1810.08647 (2018) - 2017
- [j3]Çaglar Gülçehre
On integrating a language model into neural machine translation. Comput. Speech Lang. 45: 137-148 (2017) - [c18]Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville:
Recurrent Batch Normalization. ICLR (Poster) 2017 - [c17]Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio:
Mollifying Networks. ICLR (Poster) 2017 - [c16]Çaglar Gülçehre
A robust adaptive stochastic gradient method for deep learning. IJCNN 2017: 125-132 - [c15]Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio:
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models. NIPS 2017: 5474-5483 - [c14]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: 15-25 - [c13]Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio:
Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning. Rep4NLP@ACL 2017: 228-234 - [i20]Çaglar Gülçehre, Sarath Chandar, Yoshua Bengio:
Memory Augmented Neural Networks with Wormhole Connections. CoRR abs/1701.08718 (2017) - [i19]Çaglar Gülçehre, Jose Sotelo, Marcin Moczulski, Yoshua Bengio:
A Robust Adaptive Stochastic Gradient Method for Deep Learning. CoRR abs/1703.00788 (2017) - [i18]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 abs/1705.02012 (2017) - [i17]Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio:
Gated Orthogonal Recurrent Units: On Learning to Forget. CoRR abs/1706.02761 (2017) - [i16]Çaglar Gülçehre, Francis Dutil, Adam Trischler, Yoshua Bengio:
Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder. CoRR abs/1706.05087 (2017) - [i15]Francis Dutil, Çaglar Gülçehre, Adam Trischler, Yoshua Bengio:
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models. CoRR abs/1711.10462 (2017) - 2016
- [j2]Çaglar Gülçehre, Yoshua Bengio:
Knowledge Matters: Importance of Prior Information for Optimization. J. Mach. Learn. Res. 17: 8:1-8:32 (2016) - [j1]Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre
EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10(2): 99-111 (2016) - [c12]Çaglar Gülçehre
Pointing the Unknown Words. ACL (1) 2016 - [c11]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 - [c10]Ramesh Nallapati, Bowen Zhou, Cícero Nogueira dos Santos, Çaglar Gülçehre
Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond. CoNLL 2016: 280-290 - [c9]Çaglar Gülçehre, Marcin Moczulski, Misha Denil, Yoshua Bengio:
Noisy Activation Functions. ICML 2016: 3059-3068 - [c8]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 - [i14]Çaglar Gülçehre, Marcin Moczulski, Misha Denil, Yoshua Bengio:
Noisy Activation Functions. CoRR abs/1603.00391 (2016) - [i13]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 abs/1603.06807 (2016) - [i12]Çaglar Gülçehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua Bengio:
Pointing the Unknown Words. CoRR abs/1603.08148 (2016) - [i11]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 abs/1605.02688 (2016) - [i10]Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio:
Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes. CoRR abs/1607.00036 (2016) - [i9]Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio:
Mollifying Networks. CoRR abs/1608.04980 (2016) - 2015
- [c7]Junyoung Chung, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio:
Gated Feedback Recurrent Neural Networks. ICML 2015: 2067-2075 - [i8]Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio:
Gated Feedback Recurrent Neural Networks. CoRR abs/1502.02367 (2015) - [i7]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 abs/1503.01800 (2015) - [i6]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 abs/1503.03535 (2015) - 2014
- [c6]Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. EMNLP 2014: 1724-1734 - [c5]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: 2933-2941 - [c4]Çaglar Gülçehre
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks. ECML/PKDD (1) 2014: 530-546 - [c3]Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio:
How to Construct Deep Recurrent Neural Networks. ICLR (Poster) 2014 - [i5]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 abs/1406.1078 (2014) - [i4]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 abs/1406.2572 (2014) - [i3]Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio:
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. CoRR abs/1412.3555 (2014) - [i2]Çaglar Gülçehre, Yoshua Bengio:
ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient. CoRR abs/1412.7419 (2014) - 2013
- [c2]Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre
Combining modality specific deep neural networks for emotion recognition in video. ICMI 2013: 543-550 - [c1]Çaglar Gülçehre, Yoshua Bengio:
Knowledge Matters: Importance of Prior Information for Optimization. ICLR 2013 - [i1]Çaglar Gülçehre, Kyunghyun Cho, Razvan Pascanu, Yoshua Bengio:
Learned-norm pooling for deep neural networks. CoRR abs/1311.1780 (2013)
Coauthor Index
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last updated on 2024-11-19 20:45 CET by the dblp team
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