Max Schwarzer

According to our database, Max Schwarzer authored at least 20 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training.

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

CoRR, 2024

2023

Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy.

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

CoRR, 2023

Large Language Models as Generalizable Policies for Embodied Tasks.

Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Walter Talbott, Katherine Metcalf, Natalie Mackraz, R. Devon Hjelm, Alexander Toshev

CoRR, 2023

Bigger, Better, Faster: Human-level Atari with human-level efficiency.

Max Schwarzer, Johan Samir Obando-Ceron, Aaron C. Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro

Proceedings of the International Conference on Machine Learning, 2023

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification.

Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron C. Courville

Proceedings of the Eleventh International Conference on Learning Representations, 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 C. Courville

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

To join or not to join?-A framework for the evaluation of enterprise blockchain consortia.

Max Schwarzer, Tan Gürpinar, Michael Henke

Frontiers Blockchain, July, 2022

Beyond Tabula Rasa: Reincarnating Reinforcement Learning.

Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare

CoRR, 2022

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification.

Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Kenji Kawaguchi, Ankit Vani, Aaron C. Courville

CoRR, 2022

Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress.

Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Primacy Bias in Deep Reinforcement Learning.

Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro, Pierre-Luc Bacon, Aaron C. Courville

Proceedings of the International Conference on Machine Learning, 2022

2021

Blockchain Technology in Supply Chain Management - A Discussion of Current and Future Research Topics.

Tan Gürpinar, Nick Große, Max Schwarzer, Eugen Burov, Roman Stammes, Philipp Asterios Ioannidis, Larissa Krämer, Rico Ahlbäumer, Michael Henke

Proceedings of the Science and Technologies for Smart Cities, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Reinforcement Learning at the Edge of the Statistical Precipice.

Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Iterated learning for emergent systematicity in VQA.

Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron C. Courville

Proceedings of the 9th International Conference on Learning Representations, 2021

Data-Efficient Reinforcement Learning with Self-Predictive Representations.

Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Data-Efficient Reinforcement Learning with Momentum Predictive Representations.

Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman

CoRR, 2020

GAIT: A Geometric Approach to Information Theory.

Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

GEAR: Geometry-Aware Rényi Information.

Jose Gallego-Posada, Ankit Vani, Max Schwarzer, Simon Lacoste-Julien

CoRR, 2019

2018

Learning to fail: Predicting fracture evolution in brittle materials using recurrent graph convolutional neural networks.

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

CoRR, 2018