Yulong Lu

activity

20152026

most citedA Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions

34 citations · 212 across the 40 of their papers we have counts for

collaborators

Showing math.PRShow all

4 papers · 1 filter

math.PR2019★ 22 cited

Geometric ergodicity of Langevin dynamics with Coulomb interactions

Yulong Lu, Jonathan C. Mattingly

This paper is concerned with the long time behavior of Langevin dynamics of {\em Coulomb gases} in $R^{d}$ with $d \geq 2$ , that is a second order system of Brownian particle…

math.PR2018

On the rate of convergence of empirical measure in $\infty -$ Wasserstein distance for unbounded density function

Anning Liu, Jian-Guo Liu, Yulong Lu

We consider a sequence of identically independently distributed random samples from an absolutely continuous probability measure in one dimension with unbounded density. We establi…

math.PR2016★ 4 cited

Gaussian Approximations for Probability Measures on $R^{d}$

Yulong Lu, Andrew M. Stuart, Hendrik Weber

This paper concerns the approximation of probability measures on $R^{d}$ with respect to the Kullback-Leibler divergence. Given an admissible target measure, we show the exi…

math.PR2016★ 1 cited

Gaussian approximations for transition paths in Brownian dynamics

Yulong Lu, Andrew M. Stuart, Hendrik Weber

This paper is concerned with transition paths within the framework of the overdamped Langevin dynamics model of chemical reactions. We aim to give an efficient description of typic…

Geometric ergodicity of Langevin dynamics with Coulomb interactions

On the rate of convergence of empirical measure in ∞−Wasserstein distance for unbounded density function

Gaussian Approximations for Probability Measures on Rd

Gaussian approximations for transition paths in Brownian dynamics

On the rate of convergence of empirical measure in $\infty -$ Wasserstein distance for unbounded density function

Gaussian Approximations for Probability Measures on $R^{d}$