Solving Time Dependent Fokker-Planck Equations via Temporal Normalizing Flow
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Publication:5106295
DOI10.4208/cicp.OA-2022-0090zbMath1495.65187arXiv2112.14012OpenAlexW4293659830MaRDI QIDQ5106295
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Publication date: 16 September 2022
Published in: Communications in Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2112.14012
Artificial neural networks and deep learning (68T07) Numerical solutions to stochastic differential and integral equations (65C30) Probabilistic methods, particle methods, etc. for initial value and initial-boundary value problems involving PDEs (65M75)
Related Items (6)
A New Artificial Neural Network Method for Solving Schrödinger Equations on Unbounded Domains ⋮ Adaptive deep density approximation for fractional Fokker-Planck equations ⋮ A Chebyshev Polynomial Neural Network Solver for Boundary Value Problems of Elliptic Equations ⋮ PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations ⋮ Failure-Informed Adaptive Sampling for PINNs ⋮ Self-adaptive physics-informed neural networks
Uses Software
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