| 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 | 44 | 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 | 35 | 2022 |
| 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 | 13 | 2022 |
| 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 | 12 | 2023 |
| Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs L Wu, H Lin, Y Huang, SZ Li ICML2023, 2023 | 11 | 2023 |
| Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions L Wu, H Lin, Y Huang, SZ Li IEEE TNNLS, 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 | 9 | 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 | 7 | 2023 |
| 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 | 5 | 2023 |
| 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 |
| 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 | 4 | 2024 |
| 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 | 4 | 2023 |
| 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 |
| 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 arXiv preprint arXiv:2402.08198, 2024 | 3 | 2024 |
| A survey on protein representation learning: Retrospect and prospect L Wu, Y Huang, H Lin, SZ Li arXiv preprint arXiv:2301.00813, 2022 | 3 | 2022 |
| Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks T Fan, L Wu, Y Huang, H Lin, C Tan, Z Gao, SZ Li arXiv preprint arXiv:2403.01400, 2024 | 1 | 2024 |
| MMDesign: Multi-Modality Transfer Learning for Generative Protein Design J Zheng, S Li, Y Huang, Z Gao, C Tan, B Hu, J Xia, G Wang, SZ Li arXiv preprint arXiv:2312.06297, 2023 | 1 | 2023 |
| Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions R Sun, L Wu, H Lin, Y Huang, SZ Li arXiv preprint arXiv:2403.00875, 2024 | | 2024 |
Stan Z. Li (李子青)Westlake University & CAS Institute of AutomationVerified email at westlake.edu.cn
