22 citations · 30 across the 8 of their papers we have counts for
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cs.LG2023
A Deep Learning Framework for Solving Hyperbolic Partial Differential Equations: Part I
Rajat Arora
Physics informed neural networks (PINNs) have emerged as a powerful tool to provide robust and accurate approximations of solutions to partial differential equations (PDEs). Howeve…
cs.LG2022★ 1 cited
Spatio-Temporal Super-Resolution of Dynamical Systems using Physics-Informed Deep-Learning
Rajat Arora, Ankit Shrivastava
This work presents a physics-informed deep learning-based super-resolution framework to enhance the spatio-temporal resolution of the solution of time-dependent partial differentia…
cs.LG2021★ 5 cited
Machine Learning-Accelerated Computational Solid Mechanics: Application to Linear Elasticity
Rajat Arora
This work presents a novel physics-informed deep learning based super-resolution framework to reconstruct high-resolution deformation fields from low-resolution counterparts, obtai…