| Generative causal explanations for graph neural networks W Lin, H Lan, B Li International Conference on Machine Learning, 6666-6679, 2021 | 137 | 2021 |
| Orphicx: A causality-inspired latent variable model for interpreting graph neural networks W Lin, H Lan, H Wang, B Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 47 | 2022 |
| Thor: a scalable hybrid switching architecture for data centers X Yu, H Xu, H Gu, H Lan IEEE Transactions on Communications 66 (10), 4653-4665, 2018 | 13 | 2018 |
| Accelerated device placement optimization with contrastive learning H Lan, L Chen, B Li Proceedings of the 50th International Conference on Parallel Processing, 1-10, 2021 | 12 | 2021 |
| Eagle: Expedited device placement with automatic grouping for large models H Lan, L Chen, B Li 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2021 | 6 | 2021 |
| A novel multi-controller flow schedule scheme for fat-tree architecture H Lan, L Liu, X Yu, H Gu, Y Guo 2016 15th International Conference on Optical Communications and Networks …, 2016 | 2 | 2016 |
| Rss: a relay-based schedule scheme for optical data center network S Ma, H Gu, H Lan, X Yu, K Wang Photonic Network Communications 39, 70-77, 2020 | 1 | 2020 |
| Pipeline Parallelism Optimization with Deep Reinforcement Learning H Lan, B Li, W Wei, X Yu | | 2023 |
| Graph-Relational Federated Learning: Enhanced Personalization and Robustness W Lin, H Lan, H He, B Li | | 2023 |
| Device Placement Optimization with Deep Reinforcement Learning H Lan University of Toronto (Canada), 2023 | | 2023 |
| Interpreting Graph Neural Networks via Unrevealed Causal Learning W Lin, H Lan, H Wang, B Li | | 2021 |
| OROF: A hybrid topology with high scalability for data center networks H Lan, H Gu, X Yu, X Wang 2015 14th International Conference on Optical Communications and Networks …, 2015 | | 2015 |
Wanyu LinThe Hong Kong Polytechnic University在 comp.polyu.edu.hk 的电子邮件经过验证
