| Why resampling outperforms reweighting for correcting sampling bias with stochastic gradients J An, L Ying, Y Zhu ICLR 2021, 2020 | 41 | 2020 |
| Image segmentation with dynamic artifacts detection and bias correction D Zosso, J An, J Stevick, N Takaki, M Weiss, L S Slaughter, H H Cao, ... Inverse Problems and Imaging 11 (3), 577-600, 2017 | 34 | 2017 |
| Stochastic modified equations for the asynchronous stochastic gradient descent J An, J Lu, L Ying Information and Inference: A Journal of the IMA, iaz030, 2019 | 30 | 2019 |
| Fast algorithms for integral formulations of steady-state radiative transfer equation Y Fan, J An, L Ying Journal of Computational Physics 380, 191-211, 2019 | 27 | 2019 |
| Pushed, pulled and pushmi-pullyu fronts of the Burgers-FKPP equation J An, C Henderson, L Ryzhik J. Eur. Math. Soc., 2023 | 14 | 2023 |
| Quantitative steepness, semi-FKPP reactions, and pushmi-pullyu fronts J An, C Henderson, L Ryzhik Archive for Rational Mechanics and Analysis, 2023 | 11 | 2023 |
| Global well-posedness for the Euler alignment system with mildly singular interactions J An, L Ryzhik Nonlinearity, 2019 | 5 | 2019 |
| Front location determines convergence rate to traveling waves J An, C Henderson, L Ryzhik Ann. Inst. H. Poincaré Anal. Non Linéaire, 2024 | 4 | 2024 |
| Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks J An, J Lu arXiv preprint arXiv:2304.09221, 2023 | 4 | 2023 |
| Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss P Bréchet, K Papagiannouli, J An, G Montúfar ICML 2023, 2023 | 4 | 2023 |
| Voting models and semilinear parabolic equations J An, C Henderson, L Ryzhik Nonlinearity, 2023 | 4 | 2023 |
| Why does the two-timescale Q-learning converge to different mean field solutions? A unified convergence analysis J An, J Lu, Y Wu, X Yang arXiv:2404.04357, 2024 | 2 | 2024 |
| On the gradient flow structure of the isotropic Landau equation J An, L Ying Communications in Mathematical Sciences, 2019 | 1 | 2019 |
| Combining resampling and reweighting for faithful stochastic optimization J An, L Ying Communications in Mathematical Sciences, 2022 | | 2022 |
| Nonlinear Analysis of Biological Models and Stochastic Analysis of Machine Learning Methods J An Stanford University, 2021 | | 2021 |
Lexing YingProfessor of Mathematics, Stanford UniversityVerified email at stanford.edu
