| Pdo-econvs: Partial differential operator based equivariant convolutions Z Shen, L He, Z Lin, J Ma International Conference on Machine Learning, 8697-8706, 2020 | 53 | 2020 |
| Efficient equivariant network L He, Y Chen, Y Dong, Y Wang, Z Lin Advances in Neural Information Processing Systems 34, 5290-5302, 2021 | 30 | 2021 |
| PDO-eS2CNNs: Partial differential operator based equivariant spherical CNNs Z Shen, T Shen, Z Lin, J Ma Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9585-9593, 2021 | 16 | 2021 |
| PDO-s3DCNNs: Partial differential operator based steerable 3D CNNs Z Shen, T Hong, Q She, J Ma, Z Lin International Conference on Machine Learning, 19827-19846, 2022 | 11 | 2022 |
| Inter-intra variant dual representations forself-supervised video recognition L Zhang, Q She, Z Shen, C Wang arXiv preprint arXiv:2107.01194, 2021 | 11 | 2021 |
| Neural ePDOs: Spatially adaptive equivariant partial differential operator based networks L He, Y Chen, Z Shen, Y Yang, Z Lin The Eleventh International Conference on Learning Representations, 2022 | 8 | 2022 |
| Efficient learning of Scale-Adaptive Nearly Affine Invariant Networks Z Shen, Y Qiu, J Liu, L He, Z Lin Neural Networks 174, 106229, 2024 | 1 | 2024 |
| Newton design: designing CNNs with the family of Newton’s methods Z Shen, Y Yang, Q She, C Wang, J Ma, Z Lin Science China Information Sciences 66 (6), 162101, 2023 | 1 | 2023 |
| Optimization-inspired manual architecture design and neural architecture search Y Yang, Z Shen, H Li, Z Lin Science China Information Sciences 66 (11), 212101, 2023 | | 2023 |
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR, CSIG & AAIA; ex-VP of Samsung ResearchПотвърден имейл адрес: pku.edu.cn
