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20142024
most citedNumerical Analysis on Neural Network Projected Schemes for Approximating One Dimensional Wasserstein Gradient Flows

3 citations · 14 across the 16 of their papers we have counts for

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math.OC2024

Laplace Meets Moreau: Smooth Approximation to Infimal Convolutions Using Laplace's Method

Ryan J. Tibshirani, Samy Wu Fung, Howard Heaton +1

We study approximations to the Moreau envelope -- and infimal convolutions more broadly -- based on Laplace's method, a classical tool in analysis which ties certain integrals to s…

math.OC2024

Efficient Computation of Mean field Control based Barycenters from Reaction-Diffusion Systems

Arjun Vijaywargiya, Guosheng Fu, Stanley Osher +1

We develop a class of barycenter problems based on mean field control problems in three dimensions with associated reactive-diffusion systems of unnormalized multi-species densitie…

math.OC2024

A Primal-dual hybrid gradient method for solving optimal control problems and the corresponding Hamilton-Jacobi PDEs

Tingwei Meng, Siting Liu, Wuchen Li +1

Optimal control problems are crucial in various domains, including path planning, robotics, and humanoid control, demonstrating their broad applicability. The connection between op…

math.OC20232 cited

Generalized optimal transport and mean field control problems for reaction-diffusion systems with high-order finite element computation

Guosheng Fu, Stanley Osher, Will Pazner +1

We design and compute a class of optimal control problems for reaction-diffusion systems. They form mean field control problems related to multi-density reaction-diffusion systems.…

math.OC2023

A kernel formula for regularized Wasserstein proximal operators

Wuchen Li, Siting Liu, Stanley Osher

We study a class of regularized proximal operators in Wasserstein-2 space. We derive their solutions by kernel integration formulas. We obtain the Wasserstein proximal operator usi…