| A constructive approach to L 0 penalized regression J Huang, Y Jiao, Y Liu, X Lu The Journal of Machine Learning Research 19 (1), 403-439, 2018 | 93 | 2018 |
| A primal dual active set with continuation algorithm for the -regularized optimization problem Y Jiao, B Jin, X Lu Applied and Computational Harmonic Analysis 39 (3), 400-426, 2015 | 88 | 2015 |
| Stripe noise separation and removal in remote sensing images by consideration of the global sparsity and local variational properties X Liu, X Lu, H Shen, Q Yuan, Y Jiao, L Zhang IEEE Transactions on Geoscience and Remote Sensing 54 (5), 3049-3060, 2016 | 87 | 2016 |
| Deep generative learning via schr\"{o}dinger bridge G Wang, Y Jiao, Q Xu, Y Wang, C Yang ICML, 2021 | 80 | 2021 |
| Convergence rate analysis for deep ritz method C Duan, Y Jiao, Y Lai, X Lu, Z Yang Commun. Comput. Phys. 31 (4), 1020-1048, 2021 | 67 | 2021 |
| Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors Y Jiao, G Shen, Y Lin, J Huang The Annals of Statistics 51 (2), 691-716, 2023 | 58* | 2023 |
| Alternating Direction Method of Multipliers for Linear Inverse Problems Y Jiao, Q Jin, X Lu, W Wang SIAM Journal on Numerical Analysis, 54 (4), 2114-2137, 2016 | 53 | 2016 |
| A Unified Primal Dual Active Set Algorithm for Nonconvex Sparse Recovery J Huang, Y Jiao, B Jin, J Liu, X Lu, C Yang Statistical Science 36 (2), 215-238, 2021 | 48* | 2021 |
| A primal dual active set algorithm with continuation for compressed sensing Q Fan, Y Jiao, X Lu IEEE Transactions on Signal Processing 62 (23), 6276-6285, 2014 | 47 | 2014 |
| Deep Generative Learning via Variational Gradient Flow Y Gao, Y Jiao, Y Wang, Y Wang, C Yang, S Zhang ICML, 2019 | 43 | 2019 |
| A Nonconvex Model with Minimax Concave Penalty for Image Restoration J You, Y Jiao, X Lu, T Zeng Journal of Scientific Computing 78 (2), 1063-1086, 2019 | 43 | 2019 |
| Group Sparse Recovery via the Penalty: Theory and Algorithm Y Jiao, B Jin, X Lu IEEE Transactions on Signal Processing 65 (4), 998-1012, 2017 | 42 | 2017 |
| Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST W Liu, X Liao, Z Luo, Y Yang, MC Lau, Y Jiao, X Shi, W Zhai, H Ji, ... Nature communications 14 (1), 296, 2023 | 41 | 2023 |
| Error analysis of deep Ritz methods for elliptic equations Y Jiao, Y Lai, Y Lo, Y Wang, Y Yang Analysis and Application 22 (1), 57-87, 2021 | 40 | 2021 |
| An alternating direction method with continuation for nonconvex low rank minimization ZF Jin, Z Wan, Y Jiao, X Lu Journal of Scientific Computing 66, 849-869, 2016 | 40 | 2016 |
| Preasymptotic convergence of randomized Kaczmarz method Y Jiao, B Jin, X Lu Inverse Problems 33 (12), 125012, 2017 | 38 | 2017 |
| An error analysis of generative adversarial networks for learning distributions J Huang, Y Jiao, Z Li, S Liu, Y Wang, Y Yang Journal of machine learning research 23 (116), 1-43, 2022 | 36 | 2022 |
| A rate of convergence of physics informed neural networks for the linear second order elliptic pdes Y Jiao, Y Lai, D Li, X Lu, F Wang, Y Wang, JZ Yang Communications in Computational Physics 31 (4), 1272-1295, 2021 | 36* | 2021 |
| CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies Y Yang, XJ Shi, Y Jiao, J Huang, M Chen, X Zhou, L Sun, X Lin, C Yang, ... Bioinformatics 36 (7), 2009-2016, 2020 | 31 | 2020 |
| A deep generative approach to conditional sampling X Zhou, Y Jiao, J Liu, J Huang Journal of the American Statistical Association 118 (543), 1837-1848, 2023 | 28 | 2023 |
