Simgrace: A simple framework for graph contrastive learning without data augmentation J Xia, L Wu, J Chen, B Hu, SZ Li Proceedings of the ACM Web Conference 2022, 1070-1079, 2022 | 256 | 2022 |
Mole-bert: Rethinking pre-training graph neural networks for molecules J Xia, C Zhao, B Hu, Z Gao, C Tan, Y Liu, S Li, SZ Li | 90 | 2023 |
A lightweight spatial and temporal multi-feature fusion network for defect detection B Hu, B Gao, WL Woo, L Ruan, J Jin, Y Yang, Y Yu IEEE Transactions on Image Processing 30, 472-486, 2020 | 70 | 2020 |
Generative de novo protein design with global context C Tan, Z Gao, J Xia, B Hu, SZ Li arXiv preprint arXiv:2204.10673, 2022 | 39 | 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 | 24 | 2022 |
Beyond homophily and homogeneity assumption: Relation-based frequency adaptive graph neural networks L Wu, H Lin, B Hu, C Tan, Z Gao, Z Liu, SZ Li IEEE Transactions on Neural Networks and Learning Systems, 2023 | 23 | 2023 |
Defect depth retrieval method based on nonlinear transformation for pulsed thermographic inspection M Wang, B Gao, T Wu, B Hu, L Liu International Journal of Thermal Sciences 149, 106196, 2020 | 18 | 2020 |
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 |
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 | 7 | 2024 |
Understanding the limitations of deep models for molecular property prediction: Insights and solutions J Xia, L Zhang, X Zhu, Y Liu, Z Gao, B Hu, C Tan, J Zheng, S Li, SZ Li Advances in Neural Information Processing Systems 36, 64774-64792, 2023 | 7 | 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 | 7 | 2023 |
Cross-gate mlp with protein complex invariant embedding is a one-shot antibody designer C Tan, Z Gao, L Wu, J Xia, J Zheng, X Yang, Y Liu, B Hu, SZ Li Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15222 …, 2024 | 5 | 2024 |
Segment anything in defect detection B Hu, B Gao, C Tan, T Wu, SZ Li arXiv preprint arXiv:2311.10245, 2023 | 4 | 2023 |
Global-context aware generative protein design C Tan, Z Gao, J Xia, B Hu, SZ Li ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
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 | 3 | 2023 |
Hierarchical data-efficient representation learning for tertiary structure-based rna design C Tan, Y Zhang, Z Gao, H Cao, SZ Li arXiv preprint arXiv:2301.10774, 2023 | 3 | 2023 |
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design C Tan, Y Zhang, Z Gao, B Hu, S Li, Z Liu, SZ Li The Twelfth International Conference on Learning Representations, 2024 | 2 | 2024 |
Deep manifold graph auto-encoder for attributed graph embedding B Hu, Z Zang, J Xia, L Wu, C Tan, SZ Li ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 2 | 2023 |
Wordreg: Mitigating the gap between training and inference with worst-case drop regularization J Xia, G Wang, B Hu, C Tan, J Zheng, Y Xu, SZ Li ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 2 | 2023 |
Deep Manifold Transformation for Protein Representation Learning B Hu, Z Zang, C Tan, SZ Li ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 1 | 2024 |