HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models

Fuente: arXiv

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Bibliographic Details
Main Authors:	Meng, Tingwei, Zou, Zongren, Darbon, Jérôme, Karniadakis, George Em
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Optimization and Control Computation
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2409.09614