We study the convergences of three projected Sobolev gradient flows to t...
Finding the mixed Nash equilibria (MNE) of a two-player zero sum continu...
Deep operator network (DeepONet) has demonstrated great success in vario...
Motivated by the challenge of sampling Gibbs measures with nonconvex
pot...
Spectral Barron spaces have received considerable interest recently as i...
This paper concerns solving the steady radiative transfer equation with
...
Numerical solutions to high-dimensional partial differential equations (...
This paper analyzes the generalization error of two-layer neural network...
This paper concerns the a priori generalization analysis of the Deep Rit...
In many applications, data and/or parameters are supported on non-Euclid...
This paper studies the universal approximation property of deep neural
n...
Training deep neural networks with stochastic gradient descent (SGD) can...
A fundamental problem in Bayesian inference and statistical machine lear...
Diffusion approximation provides weak approximation for stochastic gradi...
We consider a sequence of identically independently distributed random
s...
We study an interacting particle system in R^d motivated by Stein
variat...