Stochastic physics-informed neural ordinary differential equations

Jared O’Leary; Joel A. Paulson; Ali Mesbah

doi:10.1016/j.jcp.2022.111466

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Stochastic physics-informed neural ordinary differential equations

Jared O’Leary Joel A. Paulson Ali Mesbah

Year: 2022 Journal: Journal of Computational Physics Vol: 468 Pages: 111466-111466 Publisher: Elsevier BV

DOI: 10.1016/j.jcp.2022.111466

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Keywords:

Ordinary differential equation Stochastic differential equation Artificial neural network Ode Dynamical systems theory Automatic differentiation Stochastic gradient descent Stochastic neural network Statistical physics Computer science Nonlinear system Stochastic process Applied mathematics Artificial intelligence Differential equation Mathematics Algorithm Recurrent neural network Physics Mathematical analysis

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Model Reduction and Neural Networks

Physical Sciences → Physics and Astronomy → Statistical and Nonlinear Physics

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Probabilistic and Robust Engineering Design

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Stochastic physics-informed neural ordinary differential equations

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