Max Schwarzer

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Information Theory

Reinforcement Learning

Convolutional Neural Networks

General Intelligence

Top Venues

Publications

Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Rin Metcalf, Walter Talbott, Natalie Mackraz, R. Devon Hjelm, Alexander T. Toshev
Large Language Models as Generalizable Policies for Embodied Tasks. ICLR (2024)
Brandon McKinzie, Zhe Gan, Jean-Philippe Fauconnier, Sam Dodge, Bowen Zhang, Philipp Dufter, Dhruti Shah, Xianzhi Du, Futang Peng, Floris Weers, Anton Belyi, Haotian Zhang, Karanjeet Singh, Doug Kang, Ankur Jain, Hongyu Hè, Max Schwarzer, Tom Gunter, Xiang Kong, Aonan Zhang, Jianyu Wang, Chong Wang, Nan Du, Tao Lei, Sam Wiseman, Guoli Yin, Mark Lee, Zirui Wang, Ruoming Pang, Peter Grasch, Alexander Toshev, Yinfei Yang
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training. CoRR (2024)
Pierluca D'Oro, Max Schwarzer, Evgenii Nikishin, Pierre-Luc Bacon, Marc G. Bellemare, Aaron C. Courville
Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier. ICLR (2023)
Max Schwarzer, Jesse Farebrother, Joshua Greaves, Ekin Dogus Cubuk, Rishabh Agarwal, Aaron C. Courville, Marc G. Bellemare, Sergei V. Kalinin, Igor Mordatch, Pablo Samuel Castro, Kevin M. Roccapriore
Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. CoRR (2023)
Max Schwarzer, Johan S. Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
Bigger, Better, Faster: Human-level Atari with human-level efficiency. CoRR (2023)
Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron C. Courville
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. ICLR (2023)
Max Schwarzer, Johan Samir Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro
Bigger, Better, Faster: Human-level Atari with human-level efficiency. ICML (2023)
Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Walter Talbott, Katherine Metcalf, Natalie Mackraz, R. Devon Hjelm, Alexander Toshev
Large Language Models as Generalizable Policies for Embodied Tasks. CoRR (2023)
Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville
The Primacy Bias in Deep Reinforcement Learning. ICML (2022)
Max Schwarzer, Tan Gürpinar, Michael Henke
To join or not to join?-A framework for the evaluation of enterprise blockchain consortia. Frontiers Blockchain 5 (2022)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress. NeurIPS (2022)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Beyond Tabula Rasa: Reincarnating Reinforcement Learning. CoRR (2022)
Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Kenji Kawaguchi, Ankit Vani, Aaron C. Courville
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. CoRR (2022)
Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville
The Primacy Bias in Deep Reinforcement Learning. CoRR (2022)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Deep Reinforcement Learning at the Edge of the Statistical Precipice. CoRR (2021)
Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare
Deep Reinforcement Learning at the Edge of the Statistical Precipice. NeurIPS (2021)
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville
Iterated learning for emergent systematicity in VQA. CoRR (2021)
Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR (2021)
Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville
Iterated learning for emergent systematicity in VQA. ICLR (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS (2021)
Tan Gürpinar, Nick Große, Max Schwarzer, Eugen Burov, Roman Stammes, Philipp Asterios Ioannidis, Larissa Krämer, Rico Ahlbäumer, Michael Henke
Blockchain Technology in Supply Chain Management - A Discussion of Current and Future Research Topics. SmartCity360° (2021)
Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
GAIT: A Geometric Approach to Information Theory. AISTATS (2020)
Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman
Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR (2020)
Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien
GEAR: Geometry-Aware Rényi Information. CoRR (2019)
Max Schwarzer, Bryce Rogan, Yadong Ruan, Zhengming Song, Diana Lee, Allon G. Percus, Viet T. Chau, Bryan A. Moore, Esteban Rougier, Hari S. Viswanathan, Gowri Srinivasan
Learning to fail: Predicting fracture evolution in brittle materials using recurrent graph convolutional neural networks. CoRR (2018)