3 citations · 4 across the 16 of their papers we have counts for
10 papers · 1 filter
Zero-Shot Transferable Solution Method for Parametric Optimal Control Problems
Xingjian Li, Kelvin Kan, Deepanshu Verma +3
This paper presents a transferable solution method for optimal control problems with varying objectives using function encoder (FE) policies. Traditional optimization-based approac…
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…
Inexact Proximal Point Algorithms for Zeroth-Order Global Optimization
Minxin Zhang, Fuqun Han, Yat Tin Chow +2
This work concerns the zeroth-order global minimization of continuous nonconvex functions with a unique global minimizer and possibly multiple local minimizers. We formulate a theo…
Gradient-adjusted underdamped Langevin dynamics for sampling
Xinzhe Zuo, Stanley Osher, Wuchen Li
Sampling from a target distribution is a fundamental problem. Traditional Markov chain Monte Carlo (MCMC) algorithms, such as the unadjusted Langevin algorithm (ULA), derived from…
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…
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…