| DeePMD-kit v2: A software package for deep potential models J Zeng, D Zhang, D Lu, P Mo, Z Li, Y Chen, M Rynik, L Huang, Z Li, S Shi, ... The Journal of Chemical Physics 159 (5), 2023 | 236 | 2023 |
| Uni-Fold: an open-source platform for developing protein folding models beyond AlphaFold Z Li, X Liu, W Chen, F Shen, H Bi, G Ke, L Zhang bioRxiv, 2022.08. 04.502811, 2022 | 44 | 2022 |
| Kolmogorov-arnold networks are radial basis function networks Z Li arXiv preprint arXiv:2405.06721, 2024 | 36 | 2024 |
| Deep Molecular Representation Learning via Fusing Physical and Chemical Information S Yang, Z Li, G Song, L Cai Advances in Neural Information Processing Systems (NeurIPS-2021) 34, 16346-16357, 2021 | 26 | 2021 |
| Conformation-Guided Molecular Representation with Hamiltonian Neural Networks Z Li, S Yang, G Song, L Cai International Conference on Learning Representations (ICLR-2021), 2021 | 25* | 2021 |
| GCN-LASE: Towards adequately incorporating link attributes in graph convolutional networks Z Li, L Zhang, G Song International Joint Conference on Artificial Intelligence (IJCAI-2019), 2959 …, 2019 | 23 | 2019 |
| Learning node representations from noisy graph structures J Wang, Z Li, Q Long, W Zhang, G Song, C Shi 2020 IEEE international conference on data mining (ICDM), 1310-1315, 2020 | 17 | 2020 |
| SepNE: Bringing Separability to Network Embedding Z Li, L Zhang, G Song AAAI Conference on Artificial Intelligence (AAAI-2019) 33 (01), 4261-4268, 2019 | 15 | 2019 |
| Learning Discrete Adaptive Receptive Fields for Graph Convolutional Networks X Ma, Z Li, G Song, C Shi SCIENCE CHINA Information Science, 2020 | 9 | 2020 |
| Uni-Fold Symmetry: harnessing symmetry in folding large protein complexes Z Li, S Yang, X Liu, W Chen, H Wen, F Shen, G Ke, L Zhang bioRxiv, 2022.08. 30.505833, 2022 | 8 | 2022 |
| Stepping Back to SMILES transformers for fast molecular representation inference W Zhu, Z Li, L Cai, G Song arXiv preprint arXiv:2112.13305, 2021 | 6 | 2021 |
| Uni-Fold MuSSe: De Novo Protein Complex Prediction with Protein Language Models J Zhu, Z He, Z Li, G Ke, L Zhang bioRxiv, 2023.02. 14.528571, 2023 | 5 | 2023 |
| Large scale network embedding: A separable approach G Song, L Zhang, Z Li, Y Li IEEE Transactions on Knowledge and Data Engineering 34 (4), 1829-1842, 2020 | 4 | 2020 |
| A Novel User Representation Paradigm for Making Personalized Candidate Retrieval Z Liu, Y Xing, J Lian, D Lian, Z Li, X Xie arXiv preprint arXiv:1907.06323, 2019 | 4 | 2019 |
| UMD-fit: Generating Realistic Ligand Conformations for Distance-Based Deep Docking Models E Alcaide, Z Li, H Zheng, Z Gao, G Ke NeurIPS 2023 Generative AI and Biology (GenBio) Workshop, 2023 | 3 | 2023 |
| Accurate Conformation Sampling via Protein Structural Diffusion J Fan, Z Li, E Alcaide, G Ke, H Huang, W E Journal of Chemical Information and Modeling 64 (22), 8414-8426, 2024 | 2 | 2024 |
| Proteins and protein complexes prediction powered by uni-fold X Liu, W Chen, F Shen CASP15 abstracts, 143-145, 2022 | 2 | 2022 |
| Amalga: Designable Protein Backbone Generation with Folding and Inverse Folding Guidance S Chen, Z Li, X Zeng, G Ke bioRxiv, 2023.11. 07.565939, 2023 | | 2023 |
| Equivalent Distance Geometry Error for Molecular Conformation Comparison S Yang, T Wen, Z Li, G Song arXiv preprint arXiv:2201.08714, 2021 | | 2021 |
| Elaborating the Bayesian Priors in Unsupervised Graph Embedding via Graph Concepts X Ma, Z Li, S Wei, G Song International Conference on Advanced Data Mining and Applications (ADMA-2020 …, 2020 | | 2020 |
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