activity
20192024
most citedHJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models

3 citations · 7 across the 5 of their papers we have counts for

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Showing 2019Show all

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math.OC2019

Overcoming the curse of dimensionality for some Hamilton--Jacobi partial differential equations via neural network architectures

Jerome Darbon, Gabriel P. Langlois, Tingwei Meng

We propose new and original mathematical connections between Hamilton-Jacobi (HJ) partial differential equations (PDEs) with initial data and neural network architectures. Specific…

math.OC2019

On Decomposition Models in Imaging Sciences and Multi-time Hamilton-Jacobi Partial Differential Equations

Jérôme Darbon, Tingwei Meng

This paper provides new theoretical connections between multi-time Hamilton-Jacobi partial differential equations and variational image decomposition models in imaging sciences. We…