Yulong Lu
Cited by
Cited by
A universal approximation theorem of deep neural networks for expressing probability distributions
Y Lu, J Lu
Advances in neural information processing systems 33, 3094-3105, 2020
A priori generalization analysis of the deep Ritz method for solving high dimensional elliptic partial differential equations
Y Lu, J Lu, M Wang
Conference on learning theory, 3196-3241, 2021
A Bayesian level set method for geometric inverse problems
MA Iglesias, Y Lu, AM Stuart
Interfaces and free boundaries 18 (2), 181-217, 2016
Scaling limit of the Stein variational gradient descent: The mean field regime
J Lu, Y Lu, J Nolen
SIAM Journal on Mathematical Analysis 51 (2), 648-671, 2019
A mean field analysis of deep resnet and beyond: Towards provably optimization via overparameterization from depth
Y Lu, C Ma, Y Lu, J Lu, L Ying
International Conference on Machine Learning, 6426-6436, 2020
Accelerating langevin sampling with birth-death
Y Lu, J Lu, J Nolen
arXiv preprint arXiv:1905.09863, 2019
Gaussian Approximations for Probability Measures on
Y Lu, A Stuart, H Weber
SIAM/ASA Journal on Uncertainty Quantification 5 (1), 1136-1165, 2017
A priori generalization error analysis of two-layer neural networks for solving high dimensional Schrödinger eigenvalue problems
J Lu, Y Lu
Communications of the American Mathematical Society 2 (1), 1-21, 2022
Quantitative propagation of chaos in a bimolecular chemical reaction-diffusion model
TS Lim, Y Lu, JH Nolen
SIAM Journal on Mathematical Analysis 52 (2), 2098-2133, 2020
On the representation of solutions to elliptic pdes in barron spaces
Z Chen, J Lu, Y Lu
Advances in neural information processing systems 34, 6454-6465, 2021
Geometric ergodicity of Langevin dynamics with Coulomb interactions
Y Lu, JC Mattingly
Nonlinearity 33 (2), 675, 2019
The factorization method for inverse elastic scattering from periodic structures
G Hu, Y Lu, B Zhang
Inverse Problems 29 (11), 115005, 2013
Uniform-in-time weak error analysis for stochastic gradient descent algorithms via diffusion approximation
Y Feng, T Gao, L Li, JG Liu, Y Lu
arXiv preprint arXiv:1902.00635, 2019
On the bernstein-von mises theorem for high dimensional nonlinear bayesian inverse problems
Y Lu
arXiv preprint arXiv:1706.00289, 2017
Gaussian approximations for transition paths in Brownian dynamics
Y Lu, AM Stuart, H Weber
SIAM Journal on Mathematical Analysis 49 (4), 3005–3047, 2017
Exponential decay of Rényi divergence under Fokker–Planck equations
Y Cao, J Lu, Y Lu
Journal of Statistical Physics 176, 1172-1184, 2019
Two-scale gradient descent ascent dynamics finds mixed nash equilibria of continuous games: A mean-field perspective
Y Lu
International Conference on Machine Learning, 22790-22811, 2023
Solving multiscale steady radiative transfer equation using neural networks with uniform stability
Y Lu, L Wang, W Xu
Research in the Mathematical Sciences 9 (3), 45, 2022
Transfer learning enhanced deeponet for long-time prediction of evolution equations
W Xu, Y Lu, L Wang
Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10629 …, 2023
Birth–death dynamics for sampling: global convergence, approximations and their asymptotics
Y Lu, D Slepčev, L Wang
Nonlinearity 36 (11), 5731, 2023
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