activity
20192021
most citedMeasure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

math.OC2021

Connecting Hamilton--Jacobi partial differential equations with maximum a posteriori and posterior mean estimators for some non-convex priors

Jérôme Darbon, Gabriel P. Langlois, Tingwei Meng

Many imaging problems can be formulated as inverse problems expressed as finite-dimensional optimization problems. These optimization problems generally consist of minimizing the s…

cs.LG20211 cited

Measure-conditional Discriminator with Stationary Optimum for GANs and Statistical Distance Surrogates

Liu Yang, Tingwei Meng, George Em Karniadakis

We propose a simple but effective modification of the discriminators, namely measure-conditional discriminators, as a plug-and-play module for different GANs. By taking the generat…

math.NA2020

On some neural network architectures that can represent viscosity solutions of certain high dimensional Hamilton--Jacobi partial differential equations

Jérôme Darbon, Tingwei Meng

We propose novel connections between several neural network architectures and viscosity solutions of some Hamilton--Jacobi (HJ) partial differential equations (PDEs) whose Hamilton…

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…