Hjelm, R Devon

22 publications

ICLR 2025 On the Modeling Capabilities of Large Language Models for Sequential Decision Making Martin Klissarov, R Devon Hjelm, Alexander T Toshev, Bogdan Mazoure

ICLR 2024 Large Language Models as Generalizable Policies for Embodied Tasks Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Rin Metcalf, Walter Talbott, Natalie Mackraz, R Devon Hjelm, Alexander T Toshev

ICLR 2024 Poly-View Contrastive Learning Amitis Shidani, R Devon Hjelm, Jason Ramapuram, Russell Webb, Eeshan Gunesh Dhekane, Dan Busbridge

ICLR 2022 Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL Bogdan Mazoure, Ahmed M Ahmed, R Devon Hjelm, Andrey Kolobov, Patrick MacAlpine

CVPR 2022 Robust Contrastive Learning Against Noisy Views Ching-Yao Chuang, R Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song

CoLLAs 2022 Test Sample Accuracy Scales with Training Sample Density in Neural Networks Xu Ji, Razvan Pascanu, R. Devon Hjelm, Balaji Lakshminarayanan, Andrea Vedaldi

ICLR 2021 Data-Efficient Reinforcement Learning with Self-Predictive Representations Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman

AAAI 2021 Object-Centric Image Generation from Layouts Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma

NeurIPS 2021 Pretraining Representations for Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman, Aaron C. Courville

ICML 2020 An End-to-End Approach for the Verification Problem: Learning the Right Distance Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk

NeurIPS 2020 Deep Reinforcement and InfoMax Learning Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman, R Devon Hjelm

NeurIPSW 2020 Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

ICLRW 2019 Adversarial Mixup Resynthesizers Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R Devon Hjelm, Christopher Pal

ICLR 2019 Deep Graph Infomax Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R Devon Hjelm

ICLR 2019 Learning Deep Representations by Mutual Information Estimation and Maximization R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Phil Bachman, Adam Trischler, Yoshua Bengio

NeurIPS 2019 Learning Representations by Maximizing Mutual Information Across Views Philip Bachman, R Devon Hjelm, William Buchwalter

CoRL 2019 Leveraging Exploration in Off-Policy Algorithms via Normalizing Flows Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R Devon Hjelm

NeurIPS 2019 On Adversarial Mixup Resynthesis Christopher Beckham, Sina Honari, Vikas Verma, Alex M Lamb, Farnoosh Ghadiri, R Devon Hjelm, Yoshua Bengio, Chris Pal

AAAI 2019 On-Line Adaptative Curriculum Learning for GANs Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm

NeurIPS 2019 Unsupervised State Representation Learning in Atari Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm

ICLR 2018 Boundary Seeking GANs R Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho, Yoshua Bengio

ICLR 2014 Deep Learning for Neuroimaging: A Validation Study Sergey M. Plis, R. Devon Hjelm, Ruslan Salakhutdinov, Vince D. Calhoun