1 code implementation • 5 Feb 2024 • 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
As a result, it is usually necessary to reproduce the experiments from scratch, which can be time-consuming and error-prone.
1 code implementation • 24 Mar 2023 • Kinal Mehta, Anuj Mahajan, Pawan Kumar
We present marl-jax, a multi-agent reinforcement learning software package for training and evaluating social generalization of the agents.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 10 Dec 2022 • Kinal Mehta, Anuj Mahajan, Pawan Kumar
A reliable critic is central to on-policy actor-critic learning.
no code implementations • 10 Mar 2022 • Abhishek Peri, Kinal Mehta, Avneesh Mishra, Michael Milford, Sourav Garg, K. Madhava Krishna
Sparse local feature matching is pivotal for many computer vision and robotics tasks.
1 code implementation • 15 Mar 2021 • Udit Singh Parihar, Aniket Gujarathi, Kinal Mehta, Satyajit Tourani, Sourav Garg, Michael Milford, K. Madhava Krishna
The use of local detectors and descriptors in typical computer vision pipelines work well until variations in viewpoint and appearance change become extreme.
no code implementations • 27 Mar 2019 • Varun Kannadi Valloli, Kinal Mehta
Crowd management is of paramount importance when it comes to preventing stampedes and saving lives, especially in a countries like China and India where the combined population is a third of the global population.