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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

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Showing 2023Show all

3 papers · 1 filter

math.NA2023

Optimal Deep Neural Network Approximation for Korobov Functions with respect to Sobolev Norms

Yahong Yang, Yulong Lu

This paper establishes the nearly optimal rate of approximation for deep neural networks (DNNs) when applied to Korobov functions, effectively overcoming the curse of dimensionalit…

math.OC2023★ 1 cited

Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Continuous Games: A Mean-Field Perspective

Yulong Lu

Finding the mixed Nash equilibria (MNE) of a two-player zero sum continuous game is an important and challenging problem in machine learning. A canonical algorithm to finding the M…

math.NA2023★ 1 cited

On the convergence of Sobolev gradient flow for the Gross-Pitaevskii eigenvalue problem

Ziang Chen, Jianfeng Lu, Yulong Lu +1

We study the convergences of three projected Sobolev gradient flows to the ground state of the Gross-Pitaevskii eigenvalue problem. They are constructed as the gradient flows of th…