Wuchen Li

Assistant professor

University of South Carolina

United States

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Dr. Wuchen Li is an Assistant Professor at the University of South Carolina, USA. His research areas focus on advanced computational methods including mean field control problems, neural ordinary differential equations, and optimal transport theory. He has authored several articles exploring the intersection of deep learning and mathematical frameworks, particularly in relation to dynamics of complex systems and numerical algorithms.

Articles (23)

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2022

Collaborators (2)

Stanley Osher

UNITED STATES

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Hong Wang

UNITED STATES

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Wuchen Li

Research Interests

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About

Articles (23)

Tensor Train Based Sampling Algorithms for Approximating Regularized Wasserstein Proximal Operators

Score-based neural ordinary differential equations for computing mean field control problems

The Multiscale Nonlocal-in-Time Schrödinger Bridge Problem

A deep learning algorithm for computing mean field control problems via forward-backward score dynamics

Primal–dual hybrid gradient algorithms for computing time-implicit Hamilton–Jacobi equations

Deep JKO: Time-implicit particle methods for general nonlinear gradient flows

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

Diffusion hypercontractivity via generalized density manifold

A first-order computational algorithm for reaction-diffusion type equations via primal-dual hybrid gradient method

Noise-free sampling algorithms via regularized Wasserstein proximals

Mean field control of droplet dynamics with high-order finite-element computations

Langevin dynamics for the probability of finite state Markov processes

High order computation of optimal transport, mean field planning, and potential mean field games

High order spatial discretization for variational time implicit schemes: Wasserstein gradient flows and reaction-diffusion systems

Wasserstein information matrix

Controlling conservation laws I: Entropy–entropy flux

A primal-dual approach for solving conservation laws with implicit in time approximations

A kernel formula for regularized Wasserstein proximal operators

Computational mean-field information dynamics associated with reaction-diffusion equations

Dynamical Schrödinger Bridge Problems on Graphs

Mean field control problems for vaccine distribution

Controlling conservation laws II: Compressible Navier–Stokes equations

A Mean Field Game Inverse Problem

Collaborators (2)

Stanley Osher

Hong Wang

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