activity
20242026
most citedScore-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems

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

collaborators

7 papers

math.OC2026

Self-supervised In-context Operator Learning for Stochastic Mean-Field Control

Suyi Gao, Mo Zhou, Rongjie Lai

Stochastic mean-field control (MFC) provides a fundamental framework for coordinating large populations of interacting agents under uncertainty, with a wide range of applications.…

math.OC2025

Learning Mean-Field Games through Mean-Field Actor-Critic Flow

Mo Zhou, Haosheng Zhou, Ruimeng Hu

We propose the Mean-Field Actor-Critic (MFAC) flow, a continuous-time learning dynamics for solving mean-field games (MFGs), combining techniques from reinforcement learning and op…

cs.LG2025

Neural Hamilton--Jacobi Characteristic Flows for Optimal Transport

Yesom Park, Shu Liu, Mo Zhou +1

We present a novel framework for solving optimal transport (OT) problems based on the Hamilton--Jacobi (HJ) equation, whose viscosity solution uniquely characterizes the OT map. By…

math.OC2025

Simulating Fokker-Planck equations via mean field control of score-based normalizing flows

Mo Zhou, Stanley Osher, Wuchen Li

The Fokker--Planck (FP) equation governs the evolution of densities for stochastic dynamics of physical systems, such as the Langevin dynamics and the Lorenz system. This work simu…

math.OC2025

Variational conditional normalizing flows for computing second-order mean field control problems

Jiaxi Zhao, Mo Zhou, Xinzhe Zuo +1

Mean field control (MFC) problems have vast applications in artificial intelligence, engineering, and economics, while solving MFC problems accurately and efficiently in high-dimen…

math.OC2024★ 2 cited

Score-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems

Mo Zhou, Stanley Osher, Wuchen Li

Classical neural ordinary differential equations (ODEs) are powerful tools for approximating the log-density functions in high-dimensional spaces along trajectories, where neural n…

math.OC2024★ 1 cited

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

Mo Zhou, Stanley Osher, Wuchen Li

We propose a deep learning approach to compute mean field control problems with individual noises. The problem consists of the Fokker-Planck (FP) equation and the Hamilton-Jacobi-B…