15 citations · 73 across the 24 of their papers we have counts for
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cs.LG2021★ 6 cited
Stochastic Adversarial Koopman Model for Dynamical Systems
Kaushik Balakrishnan, Devesh Upadhyay
Dynamical systems are ubiquitous and are often modeled using a non-linear system of governing equations. Numerical solution procedures for many dynamical systems have existed for s…
cs.MS2021★ 8 cited
NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations
Kirill Zubov, Zoe McCarthy, Yingbo Ma +11
Physics-informed neural networks (PINNs) are an increasingly powerful way to solve partial differential equations, generate digital twins, and create neural surrogates of physical…