Gulcehre, Caglar

39 publications

ICLRW 2025 Algorithm Discovery with LLMs: Evolutionary Search Meets Reinforcement Learning Anja Šurina, Amin Mansouri, Amal Seddas, Maryna Viazovska, Emmanuel Abbe, Caglar Gulcehre

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

ICML 2025 Fleet of Agents: Coordinated Problem Solving with Large Language Models Lars Henning Klein, Nearchos Potamitis, Roland Aydin, Robert West, Caglar Gulcehre, Akhil Arora

ICLRW 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

NeurIPS 2025 One-Step Is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models Viacheslav Surkov, Chris Wendler, Antonio Mari, Mikhail Terekhov, Justin Deschenaux, Robert West, Caglar Gulcehre, David Bau

NeurIPS 2025 Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions Simon Matrenok, Skander Moalla, Caglar Gulcehre

NeurIPS 2025 RAT: Bridging RNN Efficiency and Attention Accuracy via Chunk-Based Sequence Modeling Xiuying Wei, Anunay Yadav, 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

ICMLW 2024 In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning Mikhail Terekhov, Caglar Gulcehre

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

ICMLW 2024 No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO Skander Moalla, Andrea Miele, Razvan Pascanu, Caglar Gulcehre

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

ICLR 2024 Simple Hierarchical Planning with Diffusion Chang Chen, Fei Deng, 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

NeurIPS 2023 Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models Yeongbin Kim, Gautam Singh, Junyeong Park, Caglar Gulcehre, Sungjin Ahn

ICML 2023 Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto, Samuel L Smith, Albert Gu, Anushan Fernando, Caglar Gulcehre, Razvan Pascanu, Soham De

TMLR 2022 An Empirical Study of Implicit Regularization in Deep Offline RL Caglar Gulcehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet

JMLR 2022 On Instrumental Variable Regression for Deep Offline Policy Evaluation Yutian Chen, Liyuan Xu, Caglar Gulcehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet

NeurIPS 2021 Active Offline Policy Selection Ksenia Konyushova, Yutian Chen, Thomas Paine, Caglar Gulcehre, Cosmin Paduraru, Daniel J Mankowitz, Misha Denil, Nando de Freitas

NeurIPSW 2021 StarCraft II Unplugged: Large Scale Offline Reinforcement Learning Michael Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Caglar Gulcehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Konrad Zolna, Richard Powell, Julian Schrittwieser, David Choi, Petko Georgiev, Daniel Kenji Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aaron van den Oord, Wojciech M. Czarnecki, Nando de Freitas, Oriol Vinyals

NeurIPS 2020 Critic Regularized Regression Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh S Merel, Jost Tobias Springenberg, Scott E Reed, Bobak Shahriari, Noah Siegel, Caglar Gulcehre, Nicolas Heess, Nando de Freitas

ICML 2020 Improving the Gating Mechanism of Recurrent Neural Networks Albert Gu, Caglar Gulcehre, Thomas Paine, Matt Hoffman, Razvan Pascanu

ICLR 2020 Making Efficient Use of Demonstrations to Solve Hard Exploration Problems Tom Le Paine, Caglar Gulcehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team

NeurIPS 2020 RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez, Konrad Zolna, Rishabh Agarwal, Josh S Merel, Daniel J Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas

ICML 2020 Stabilizing Transformers for Reinforcement Learning Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell

ICLR 2019 Hyperbolic Attention Networks Caglar Gulcehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas

ICLR 2019 Sample Efficient Adaptive Text-to-Speech Yutian Chen, Yannis Assael, Brendan Shillingford, David Budden, Scott Reed, Heiga Zen, Quan Wang, Luis C. Cobo, Andrew Trask, Ben Laurie, Caglar Gulcehre, Aäron van den Oord, Oriol Vinyals, Nando de Freitas

ICML 2019 Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Caglar Gulcehre, Pedro Ortega, Dj Strouse, Joel Z. Leibo, Nando De Freitas

ICLR 2017 Mollifying Networks Çaglar Gülçehre, Marcin Moczulski, Francesco Visin, Yoshua Bengio

NeurIPS 2017 Plan, Attend, Generate: Planning for Sequence-to-Sequence Models Caglar Gulcehre, Francis Dutil, Adam Trischler, Yoshua Bengio

ICLR 2017 Recurrent Batch Normalization Tim Cooijmans, Nicolas Ballas, César Laurent, Çaglar Gülçehre, Aaron C. Courville

JMLR 2016 Knowledge Matters: Importance of Prior Information for Optimization Çağlar Gülçehre, Yoshua Bengio

ICML 2016 Noisy Activation Functions Caglar Gulcehre, Marcin Moczulski, Misha Denil, Yoshua Bengio

ICLR 2016 Policy Distillation Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell

ICML 2015 Gated Feedback Recurrent Neural Networks Junyoung Chung, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio

ICLR 2014 How to Construct Deep Recurrent Neural Networks Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio

NeurIPS 2014 Identifying and Attacking the Saddle Point Problem in High-Dimensional Non-Convex Optimization Yann N. Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio

ECML-PKDD 2014 Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks Çaglar Gülçehre, KyungHyun Cho, Razvan Pascanu, Yoshua Bengio

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