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 | 185 | 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 | 109* | 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 | 97 | 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 | 94 | 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 | 91 | 2020 |
Accelerating langevin sampling with birth-death Y Lu, J Lu, J Nolen arXiv preprint arXiv:1905.09863, 2019 | 45 | 2019 |
Gaussian Approximations for Probability Measures on Y Lu, A Stuart, H Weber SIAM/ASA Journal on Uncertainty Quantification 5 (1), 1136-1165, 2017 | 36 | 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 | 35 | 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 | 35 | 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 | 34 | 2021 |
Geometric ergodicity of Langevin dynamics with Coulomb interactions Y Lu, JC Mattingly Nonlinearity 33 (2), 675, 2019 | 31 | 2019 |
The factorization method for inverse elastic scattering from periodic structures G Hu, Y Lu, B Zhang Inverse Problems 29 (11), 115005, 2013 | 31 | 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 | 28 | 2019 |
On the bernstein-von mises theorem for high dimensional nonlinear bayesian inverse problems Y Lu arXiv preprint arXiv:1706.00289, 2017 | 23 | 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 | 22 | 2017 |
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 | 20 | 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 | 19 | 2022 |
Exponential decay of Rényi divergence under Fokker–Planck equations Y Cao, J Lu, Y Lu Journal of Statistical Physics 176, 1172-1184, 2019 | 19 | 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 | 18 | 2023 |
Birth–death dynamics for sampling: global convergence, approximations and their asymptotics Y Lu, D Slepčev, L Wang Nonlinearity 36 (11), 5731, 2023 | 15 | 2023 |