João G. M. Araújo

According to our database, João G. M. Araújo authored at least 6 papers between 2021 and 2024.

Collaborative distances:

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

2024

Categorical Deep Learning: An Algebraic Theory of Architectures.

Bruno Gavranovic, Paul Lessard, Andrew Dudzik, Tamara von Glehn, João G. M. Araújo, Petar Velickovic

CoRR, 2024

Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.

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

CoRR, 2024

2022

CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms.

Shengyi Huang, Rousslan Fernand Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, João G. M. Araújo

J. Mach. Learn. Res., 2022

Scalable Training of Language Models using JAX pjit and TPUv4.

Joanna Yoo, Kuba Perlin, Siddhartha Rao Kamalakara, João G. M. Araújo

CoRR, 2022

2021

No News is Good News: A Critique of the One Billion Word Benchmark.

Helen Ngo, João G. M. Araújo, Jeffrey Hui, Nicholas Frosst

CoRR, 2021

Mitigating harm in language models with conditional-likelihood filtration.

Helen Ngo, Cooper Raterink, João G. M. Araújo, Ivan Zhang, Carol Chen, Adrien Morisot, Nicholas Frosst

CoRR, 2021