187 citations · 236 across the 10 of their papers we have counts for
5 papers · 1 filter
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
Mathieu Laurière, Sarah Perrin, Sertan Girgin +8
Mean Field Games (MFGs) have been introduced to efficiently approximate games with very large populations of strategic agents. Recently, the question of learning equilibria in MFGs…
Variance Penalized On-Policy and Off-Policy Actor-Critic
Arushi Jain, Gandharv Patil, Ayush Jain +2
Reinforcement learning algorithms are typically geared towards optimizing the expected return of an agent. However, in many practical applications, low variance in the return is de…
Deep learning via LSTM models for COVID-19 infection forecasting in India
Rohitash Chandra, Ayush Jain, Divyanshu Singh Chauhan
The COVID-19 pandemic continues to have major impact to health and medical infrastructure, economy, and agriculture. Prominent computational and mathematical models have been unrel…
Generalization to New Actions in Reinforcement Learning
Ayush Jain, Andrew Szot, Joseph J. Lim
A fundamental trait of intelligence is the ability to achieve goals in the face of novel circumstances, such as making decisions from new action choices. However, standard reinforc…
NukeBERT: A Pre-trained language model for Low Resource Nuclear Domain
Ayush Jain, N. M. Meenachi, B. Venkatraman
Significant advances have been made in recent years on Natural Language Processing with machines surpassing human performance in many tasks, including but not limited to Question A…