Schwarzer, Max

13 publications

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

ICML 2023 Bigger, Better, Faster: Human-Level Atari with Human-Level Efficiency Max Schwarzer, Johan Samir Obando Ceron, Aaron Courville, Marc G Bellemare, Rishabh Agarwal, Pablo Samuel Castro

NeurIPSW 2023 Learning Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy Max Schwarzer, Jesse Farebrother, Joshua Greaves, Kevin Roccapriore, Ekin Cubuk, Rishabh Agarwal, Aaron Courville, Marc Bellemare, Sergei Kalinin, Igor Mordatch, Pablo Castro

ICLR 2023 Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G Bellemare, Aaron Courville

ICLR 2023 Simplicial Embeddings in Self-Supervised Learning and Downstream Classification Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron Courville

NeurIPS 2022 Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc Bellemare

NeurIPSW 2022 Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G Bellemare, Aaron Courville

ICML 2022 The Primacy Bias in Deep Reinforcement Learning Evgenii Nikishin, Max Schwarzer, Pierluca D’Oro, Pierre-Luc Bacon, Aaron Courville

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

NeurIPS 2021 Deep Reinforcement Learning at the Edge of the Statistical Precipice Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc Bellemare

ICLR 2021 Iterated Learning for Emergent Systematicity in VQA Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville

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

AISTATS 2020 GAIT: A Geometric Approach to Information Theory Jose Gallego Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien