3 papers
cs.LG2026
Deepmechanics
Abhay Shinde, Aryan Amit Barsainyan, Jose Siguenza +3
Physics-informed deep learning models have emerged as powerful tools for learning dynamical systems. These models directly encode physical principles into network architectures. Ho…
cond-mat.mtrl-sci2026
A fully differentiable framework for training proxy Exchange Correlation Functionals for periodic systems
Rakshit Kumar Singh, Aryan Amit Barsainyan, Bharath Ramsundar
Density Functional Theory (DFT) is widely used for first-principles simulations in chemistry and materials science, but its computational cost remains a key limitation for large sy…
cs.LG2025
STORI: A Benchmark and Taxonomy for Stochastic Environments
Aryan Amit Barsainyan, Jing Yu Lim, Dianbo Liu
Reinforcement learning (RL) techniques have achieved impressive performance on simulated benchmarks such as Atari100k, yet recent advances remain largely confined to simulation and…