| Diffbp: Generative diffusion of 3d molecules for target protein binding H Lin, Y Huang, M Liu, X Li, S Ji, SZ Li arXiv preprint arXiv:2211.11214, 2022 | 57 | 2022 |
| Knowledge distillation improves graph structure augmentation for graph neural networks L Wu, H Lin, Y Huang, SZ Li Advances in Neural Information Processing Systems 35, 11815-11827, 2022 | 43 | 2022 |
| Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs L Wu, H Lin, Y Huang, SZ Li ICML2023, 2023 | 24 | 2023 |
| Extracting Low-/High-Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework L Wu, H Lin, Y Huang, T Fan, SZ Li AAAI 2023, 2023 | 21 | 2023 |
| Protein language models and structure prediction: Connection and progression B Hu, J Xia, J Zheng, C Tan, Y Huang, Y Xu, SZ Li arXiv preprint arXiv:2211.16742, 2022 | 19 | 2022 |
| Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings J Zheng, Y Wang, G Wang, J Xia, Y Huang, G Zhao, Y Zhang, SZ Li ACL 2022, 2022 | 17 | 2022 |
| Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions L Wu, H Lin, Y Huang, SZ Li IEEE TNNLS, 2023 | 15 | 2023 |
| Mape-ppi: Towards effective and efficient protein-protein interaction prediction via microenvironment-aware protein embedding L Wu, Y Tian, Y Huang, S Li, H Lin, NV Chawla, SZ Li arXiv preprint arXiv:2402.14391, 2024 | 11 | 2024 |
| Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration H Lin, Y Huang, H Zhang, L Wu, S Li, Z Chen, SZ Li Neurips 2023, 2023 | 11 | 2023 |
| Data-efficient protein 3d geometric pretraining via refinement of diffused protein structure decoy Y Huang, L Wu, H Lin, J Zheng, G Wang, SZ Li arXiv preprint arXiv:2302.10888, 2023 | 10 | 2023 |
| Learning complete protein representation by deep coupling of sequence and structure B Hu, C Tan, J Xia, J Zheng, Y Huang, L Wu, Y Liu, Y Xu, SZ Li bioRxiv, 2023.07. 05.547769, 2023 | 9 | 2023 |
| Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction Y Huang, S Li, J Su, L Wu, O Zhang, H Lin, J Qi, Z Liu, Z Gao, Y Liu, ... AAAI 2024, 2023 | 7 | 2023 |
| Psc-cpi: Multi-scale protein sequence-structure contrasting for efficient and generalizable compound-protein interaction prediction L Wu, Y Huang, C Tan, Z Gao, B Hu, H Lin, Z Liu, SZ Li Proceedings of the AAAI Conference on Artificial Intelligence 38 (1), 310-319, 2024 | 6 | 2024 |
| A survey on protein representation learning: Retrospect and prospect L Wu, Y Huang, H Lin, SZ Li arXiv preprint arXiv:2301.00813, 2022 | 5 | 2022 |
| Non-equispaced fourier neural solvers for pdes H Lin, L Wu, Y Xu, Y Huang, S Li, G Zhao, SZ Li arXiv preprint arXiv:2212.04689, 2022 | 5 | 2022 |
| Uniif: Unified molecule inverse folding Z Gao, J Wang, C Tan, L Wu, Y Huang, S Li, Z Ye, SZ Li arXiv preprint arXiv:2405.18968, 2024 | 4 | 2024 |
| Lightweight contrastive protein structure-sequence transformation J Zheng, G Wang, Y Huang, B Hu, S Li, C Tan, X Fan, SZ Li arXiv preprint arXiv:2303.11783, 2023 | 4 | 2023 |
| Automated graph self-supervised learning via multi-teacher knowledge distillation L Wu, Y Huang, H Lin, Z Liu, T Fan, SZ Li arXiv preprint arXiv:2210.02099, 2022 | 4 | 2022 |
| Deep geometry handling and fragment-wise molecular 3d graph generation O Zhang, Y Huang, S Cheng, M Yu, X Zhang, H Lin, Y Zeng, M Wang, ... arXiv preprint arXiv:2404.00014, 2024 | 3 | 2024 |
| Foldtoken: Learning protein language via vector quantization and beyond Z Gao, C Tan, J Wang, Y Huang, L Wu, SZ Li arXiv preprint arXiv:2403.09673, 2024 | 3 | 2024 |
Stan Z. Li (李子青)Westlake University & CAS Institute of Automation在 westlake.edu.cn 的电子邮件经过验证
