| Embedding principle: a hierarchical structure of loss landscape of deep neural networks Y Zhang, Y Li, Z Zhang, T Luo, ZQJ Xu arXiv preprint arXiv:2111.15527, 2021 | 27 | 2021 |
| Towards an understanding of residual networks using neural tangent hierarchy (NTH) Y Li, T Luo, NK Yip arXiv preprint arXiv:2007.03714, 2020 | 7 | 2020 |
| Phase diagram of initial condensation for two-layer neural networks Z Chen, Y Li, T Luo, Z Zhou, ZQJ Xu arXiv preprint arXiv:2303.06561, 2023 | 6 | 2023 |
| Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural Networks Y Li, T Luo, C Ma SIAM Journal on Mathematics of Data Science 4 (2), 694-720, 2022 | 3 | 2022 |
| Stochastic modified equations and dynamics of dropout algorithm Z Zhang, Y Li, T Luo, ZQJ Xu arXiv preprint arXiv:2305.15850, 2023 | 2 | 2023 |
| Understanding the initial condensation of convolutional neural networks Z Zhou, H Zhou, Y Li, ZQJ Xu arXiv preprint arXiv:2305.09947, 2023 | 2 | 2023 |
| Demystifying Lazy Training of Neural Networks from a Macroscopic Viewpoint Y Li, T Luo, Q Zhou arXiv preprint arXiv:2404.04859, 2024 | | 2024 |
| Numerical Stability for Differential Equations with Memory G Wang, Y Li, T Luo, Z Ma, NK Yip, G Lin arXiv preprint arXiv:2305.06571, 2023 | | 2023 |
| Towards an Understanding of Residual Networks Using Neural Tangent Hierarchy Y Li Purdue University, 2021 | | 2021 |
