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João G. M. Araújo
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2020 – today
- 2024
- [c1]Bruno Gavranovic, Paul Lessard, Andrew Joseph Dudzik, Tamara von Glehn, João Guilherme Madeira Araújo, Petar Velickovic:
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures. ICML 2024 - [i7]Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad H. Danesh, Cyril Roumégous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João G. M. Araújo, Guorui Quan, Daniel Tan, Timo Klein, Rujikorn Charakorn, Mark Towers, Yann Berthelot, Kinal Mehta, Dipam Chakraborty, Arjun KG, Valentin Charraut, Chang Ye, Zichen Liu, Lucas N. Alegre, Alexander Nikulin, Xiao Hu, Tianlin Liu, Jongwook Choi, Brent Yi:
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning. CoRR abs/2402.03046 (2024) - [i6]Bruno Gavranovic, Paul Lessard, Andrew Dudzik, Tamara von Glehn, João G. M. Araújo, Petar Velickovic:
Categorical Deep Learning: An Algebraic Theory of Architectures. CoRR abs/2402.15332 (2024) - [i5]Federico Barbero, Andrea Banino, Steven Kapturowski, Dharshan Kumaran, João G. M. Araújo, Alex Vitvitskyi, Razvan Pascanu, Petar Velickovic:
Transformers need glasses! Information over-squashing in language tasks. CoRR abs/2406.04267 (2024) - [i4]Johan S. Obando-Ceron, João G. M. Araújo, Aaron C. Courville, Pablo Samuel Castro:
On the consistency of hyper-parameter selection in value-based deep reinforcement learning. CoRR abs/2406.17523 (2024) - 2022
- [j1]Shengyi Huang, Rousslan Fernand Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, João G. M. Araújo:
CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms. J. Mach. Learn. Res. 23: 274:1-274:18 (2022) - [i3]Joanna Yoo, Kuba Perlin, Siddhartha Rao Kamalakara, João G. M. Araújo:
Scalable Training of Language Models using JAX pjit and TPUv4. CoRR abs/2204.06514 (2022) - 2021
- [i2]Helen Ngo, Cooper Raterink, João G. M. Araújo, Ivan Zhang, Carol Chen, Adrien Morisot, Nicholas Frosst:
Mitigating harm in language models with conditional-likelihood filtration. CoRR abs/2108.07790 (2021) - [i1]Helen Ngo, João G. M. Araújo, Jeffrey Hui, Nicholas Frosst:
No News is Good News: A Critique of the One Billion Word Benchmark. CoRR abs/2110.12609 (2021)
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last updated on 2024-10-07 22:13 CEST by the dblp team
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