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; et al. (ICMI, 2013)

Learned-norm pooling for deep neural networks. - Çaglar Gülçehre; Kyunghyun Cho; Razvan Pascanu; Yoshua Bengio (CoRR, 2013)

Knowledge Matters: Importance of Prior Information for Optimization - Çaglar Gülçehre; Yoshua Bengio (ICLR, 2013)

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 (EMNLP, 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 (NIPS, 2014)

Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks. - Çaglar Gülçehre; KyungHyun Cho; Razvan Pascanu; Yoshua Bengio (ECML/PKDD (1), 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)

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. - Junyoung Chung; Çaglar Gülçehre; KyungHyun Cho; Yoshua Bengio (CoRR, 2014)

ADASECANT: Robust Adaptive Secant Method for Stochastic Gradient. - Çaglar Gülçehre; Yoshua Bengio (CoRR, 2014)

How to Construct Deep Recurrent Neural Networks. - Razvan Pascanu; Çaglar Gülçehre; Kyunghyun Cho; Yoshua Bengio (ICLR (Poster), 2014)

Gated Feedback Recurrent Neural Networks. - Junyoung Chung; Çaglar Gülçehre; Kyunghyun Cho; Yoshua Bengio (ICML, 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)

Pointing the Unknown Words. - Çaglar Gülçehre; Sungjin Ahn; Ramesh Nallapati; Bowen Zhou 002; Yoshua Bengio (ACL (1), 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 (ACL (1), 2016)

Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond. - Ramesh Nallapati; Bowen Zhou 002; Cícero Nogueira dos Santos; Çaglar Gülçehre; Bing Xiang (CoNLL, 2016)

Noisy Activation Functions. - Çaglar Gülçehre; Marcin Moczulski; Misha Denil; Yoshua Bengio (ICML, 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; et al. (CoRR, 2016)

Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes. - Çaglar Gülçehre; Sarath Chandar; Kyunghyun Cho; Yoshua Bengio (CoRR, 2016)

Policy Distillation. - Andrei A. Rusu; Sergio Gomez Colmenarejo; Çaglar Gülçehre; Guillaume Desjardins; James Kirkpatrick; Razvan Pascanu; Volodymyr Mnih; Koray Kavukcuoglu; Raia Hadsell (ICLR (Poster), 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; et al. (J. Multimodal User Interfaces, 2016)

Recurrent Batch Normalization. - Tim Cooijmans; Nicolas Ballas; César Laurent; Çaglar Gülçehre; Aaron C. Courville (ICLR (Poster), 2017)

Mollifying Networks. - Çaglar Gülçehre; Marcin Moczulski; Francesco Visin; Yoshua Bengio (ICLR (Poster), 2017)

A robust adaptive stochastic gradient method for deep learning. - Çaglar Gülçehre; Jose Sotelo; Marcin Moczulski; Yoshua Bengio (IJCNN, 2017)

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models. - Çaglar Gülçehre; Francis Dutil; Adam Trischler; Yoshua Bengio (NIPS, 2017)

Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning. - Çaglar Gülçehre; Francis Dutil; Adam Trischler; Yoshua Bengio (Rep4NLP@ACL, 2017)

Machine Comprehension by Text-to-Text Neural Question Generation. - Xingdi Yuan; Tong Wang 012; Çaglar Gülçehre; Alessandro Sordoni; Philip Bachman; Saizheng Zhang; Sandeep Subramanian; Adam Trischler (Rep4NLP@ACL, 2017)

Memory Augmented Neural Networks with Wormhole Connections. - Çaglar Gülçehre; Sarath Chandar; Yoshua Bengio (CoRR, 2017)

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder. - Çaglar Gülçehre; Francis Dutil; Adam Trischler; Yoshua Bengio (CoRR, 2017)

On integrating a language model into neural machine translation. - Çaglar Gülçehre; Orhan Firat; Kelvin Xu; Kyunghyun Cho; Yoshua Bengio (Comput. Speech Lang., 2017)

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 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. - Natasha Jaques; Angeliki Lazaridou; Edward Hughes 001; Çaglar Gülçehre; Pedro A. Ortega; DJ Strouse; Joel Z. Leibo; Nando de Freitas (CoRR, 2018)

Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. - Çaglar Gülçehre; Sarath Chandar; Kyunghyun Cho; Yoshua Bengio (Neural Comput., 2018)

Sample Efficient Adaptive Text-to-Speech. - Yutian Chen 001; 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; et al. (ICLR (Poster), 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 (ICLR (Poster), 2019)

Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. - Natasha Jaques; Angeliki Lazaridou; Edward Hughes 001; Çaglar Gülçehre; Pedro A. Ortega; DJ Strouse; Joel Z. Leibo; Nando de Freitas (ICML, 2019)

Improving the Gating Mechanism of Recurrent Neural Networks. - Albert Gu; Çaglar Gülçehre; Tom Le Paine; Matthew W. Hoffman; Razvan Pascanu (CoRR, 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; et al. (Nat., 2019)

Gated Orthogonal Recurrent Units: On Learning to Forget. - Li Jing 001; Çaglar Gülçehre; John Peurifoy; Yichen Shen 001; Max Tegmark; Marin Soljacic; Yoshua Bengio (Neural Comput., 2019)

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. - Çaglar Gülçehre; Tom Le Paine; Bobak Shahriari; Misha Denil; Matt Hoffman 001; Hubert Soyer; Richard Tanburn; Steven Kapturowski; Neil C. Rabinowitz; Duncan Williams; Gabriel Barth-Maron; Ziyu Wang 001; et al. (ICLR, 2020)

Improving the Gating Mechanism of Recurrent Neural Networks. - Albert Gu; Çaglar Gülçehre; Thomas Paine; Matt Hoffman 001; Razvan Pascanu (ICML, 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; et al. (ICML, 2020)

Critic Regularized Regression. - Ziyu Wang 001; Alexander Novikov 001; Konrad Zolna; Josh Merel; Jost Tobias Springenberg; Scott E. Reed; Bobak Shahriari; Noah Y. Siegel; Çaglar Gülçehre; Nicolas Heess; Nando de Freitas (NeurIPS, 2020)

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Thomas Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (NeurIPS, 2020)

Acme: A Research Framework for Distributed Reinforcement Learning. - Matt Hoffman 001; 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 001; et al. (CoRR, 2020)

RL Unplugged: Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Tom Le Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (CoRR, 2020)

Hyperparameter Selection for Offline Reinforcement Learning. - Tom Le Paine; Cosmin Paduraru; Andrea Michi; Çaglar Gülçehre; Konrad Zolna; Alexander Novikov 001; Ziyu Wang 001; Nando de Freitas (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)

Offline Learning from Demonstrations and Unlabeled Experience. - Konrad Zolna; Alexander Novikov 001; Ksenia Konyushkova; Çaglar Gülçehre; Ziyu Wang 001; Yusuf Aytar; Misha Denil; Nando de Freitas; Scott E. Reed (CoRR, 2020)

Active Offline Policy Selection. - Ksenia Konyushkova; Yutian Chen 001; Thomas Paine; Çaglar Gülçehre; Cosmin Paduraru; Daniel J. Mankowitz; Misha Denil; Nando de Freitas (NeurIPS, 2021)

Regularized Behavior Value Estimation. - Çaglar Gülçehre; Sergio Gómez Colmenarejo; Ziyu Wang 001; Jakub Sygnowski; Thomas Paine; Konrad Zolna; Yutian Chen 001; Matthew W. Hoffman; Razvan Pascanu; Nando de Freitas (CoRR, 2021)

On Instrumental Variable Regression for Deep Offline Policy Evaluation. - Yutian Chen 001; Liyuan Xu; Çaglar Gülçehre; Tom Le Paine; Arthur Gretton; Nando de Freitas; Arnaud Doucet (J. Mach. Learn. Res., 2022)

An empirical study of implicit regularization in deep offline RL. - Çaglar Gülçehre; Srivatsan Srinivasan; Jakub Sygnowski; Georg Ostrovski; Mehrdad Farajtabar; Matthew Hoffman 002; Razvan Pascanu; Arnaud Doucet (Trans. Mach. Learn. Res., 2022)

Resurrecting Recurrent Neural Networks for Long Sequences. - Antonio Orvieto; Samuel L. Smith; Albert Gu; Anushan Fernando; Çaglar Gülçehre; Razvan Pascanu; Soham De (ICML, 2023)

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models. - Yeongbin Kim; Gautam Singh; Junyeong Park; Çaglar Gülçehre; Sungjin Ahn (NeurIPS, 2023)

On the Universality of Linear Recurrences Followed by Nonlinear Projections. - Antonio Orvieto; Soham De; Çaglar Gülçehre; Razvan Pascanu; Samuel L. Smith (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; et al. (CoRR, 2023)

Reinforced Self-Training (ReST) for Language Modeling. - Çaglar Gülçehre; Tom Le Paine; Srivatsan Srinivasan; Ksenia Konyushkova; Lotte Weerts; Abhishek Sharma 015; Aditya Siddhant; Alex Ahern; Miaosen Wang; Chenjie Gu; Wolfgang Macherey; Arnaud Doucet; et al. (CoRR, 2023)

Self-Recognition in Language Models. - Tim R. Davidson; Viacheslav Surkov; Veniamin Veselovsky; Giuseppe Russo Latona; Robert West 001; Caglar Gulcehre (EMNLP (Findings), 2024)

Aligning Large Language Models with Diverse Political Viewpoints. - Dominik Stammbach; Philine Widmer; Eunjung Cho; Caglar Gulcehre; Elliott Ash (EMNLP, 2024)

Simple Hierarchical Planning with Diffusion. - Chang Chen; Fei Deng 001; Kenji Kawaguchi; Caglar Gulcehre; Sungjin Ahn (ICLR, 2024)

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. - Chang Chen; Junyeob Baek; Fei Deng 001; Kenji Kawaguchi; Caglar Gulcehre; Sungjin Ahn (ICML, 2024)

Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues. - Antonio Orvieto; Soham De; Caglar Gulcehre; Razvan Pascanu; Samuel L. Smith (ICML, 2024)

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO. - Skander Moalla; Andrea Miele; Daniil Pyatko; Razvan Pascanu; Caglar Gulcehre (NeurIPS, 2024)

Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers. - Xiuying Wei; Skander Moalla; Razvan Pascanu; Caglar Gulcehre (NeurIPS, 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 001; Srivatsan Srinivasan; Guillaume Desjardins; Arnaud Doucet; et al. (CoRR, 2024)

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO. - Skander Moalla; Andrea Miele; Razvan Pascanu; Caglar Gulcehre (CoRR, 2024)

Fleet of Agents: Coordinated Problem Solving with Large Language Models using Genetic Particle Filtering. - Akhil Arora 001; Lars Henning Klein; Nearchos Potamitis; Roland Aydin; Caglar Gulcehre; Robert West 001 (CoRR, 2024)

Promises, Outlooks and Challenges of Diffusion Language Modeling. - Justin Deschenaux; Caglar Gulcehre (CoRR, 2024)

Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers. - Xiuying Wei; Skander Moalla; Razvan Pascanu; Caglar Gulcehre (CoRR, 2024)

HiPPO-Prophecy: State-Space Models can Provably Learn Dynamical Systems in Context. - Federico Arangath Joseph; Kilian Konstantin Haefeli; Noah Liniger; Caglar Gulcehre (CoRR, 2024)

Investigating Low-Rank Training in Transformer Language Models: Efficiency and Scaling Analysis. - Xiuying Wei; Skander Moalla; Razvan Pascanu; Caglar Gulcehre (CoRR, 2024)

In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning. - Mikhail Terekhov; Caglar Gulcehre (CoRR, 2024)

The Role of Deep Learning Regularizations on Actors in Offline RL. - Denis Tarasov; Anja Surina; Caglar Gulcehre (CoRR, 2024)

Unpacking SDXL Turbo: Interpreting Text-to-Image Models with Sparse Autoencoders. - Viacheslav Surkov; Chris Wendler; Mikhail Terekhov; Justin Deschenaux; Robert West 001; Caglar Gulcehre (CoRR, 2024)

The Effect of Scheduling and Preemption on the Efficiency of LLM Inference Serving. - Kyoungmin Kim 002; Kijae Hong; Caglar Gulcehre; Anastasia Ailamaki (CoRR, 2024)

SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning. - Shivam Adarsh; Kumar Shridhar; Caglar Gulcehre; Nicholas Monath; Mrinmaya Sachan (ACL (Findings), 2025)

Beyond Autoregression: Fast LLMs via Self-Distillation Through Time. - Justin Deschenaux; Caglar Gulcehre (ICLR, 2025)

Regret-Optimized Portfolio Enhancement through Deep Reinforcement Learning and Future Looking Rewards. - Daniil Karzanov; Rubén Garzón; Mikhail Terekhov; Caglar Gulcehre; Thomas Raffinot; Marcin Detyniecki (CoRR, 2025)

From Markov to Laplace: How Mamba In-Context Learns Markov Chains. - Marco Bondaschi; Nived Rajaraman; Xiuying Wei; Kannan Ramchandran; Razvan Pascanu; Caglar Gulcehre; Michael Gastpar; Ashok Vardhan Makkuva (CoRR, 2025)

Context-Aware Toxicity Detection in Multiplayer Games: Integrating Domain-Adaptive Pretraining and Match Metadata. - Adrien Schurger-Foy; Rafal Kocielnik; Caglar Gulcehre; R. Michael Alvarez (CoRR, 2025)

Algorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning. - Anja Surina; Amin Mansouri; Lars Quaedvlieg; Amal Seddas; Maryna Viazovska; Emmanuel Abbe; Caglar Gulcehre (CoRR, 2025)

Partition Generative Modeling: Masked Modeling Without Masks. - Justin Deschenaux; Lan Tran; Caglar Gulcehre (CoRR, 2025)

Control Tax: The Price of Keeping AI in Check. - Mikhail Terekhov; Zhen Ning David Liu; Caglar Gulcehre; Samuel Albanie (CoRR, 2025)

The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset. - Gilad Landau; Miran Özdogan; Gereon Elvers; Francesco Mantegna; Pratik Somaiya; Dulhan Jayalath; Luisa Kurth; Teyun Kwon; Brendan Shillingford; Gregory Farquhar; Minqi Jiang; Karim Jerbi; et al. (CoRR, 2025)

RAT: Bridging RNN Efficiency and Attention Accuracy in Language Modeling. - Xiuying Wei; Anunay Yadav; Razvan Pascanu; Caglar Gulcehre (CoRR, 2025)

Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions. - Simon Matrenok; Skander Moalla; Caglar Gulcehre (CoRR, 2025)