Spherical Message Passing for 3D Molecular Graphs Y Liu*, L Wang*, M Liu, Y Lin, X Zhang, B Oztekin, S Ji International Conference on Learning Representations, 2022 | 147* | 2022 |
DIG: A turnkey library for diving into graph deep learning research M Liu*, Y Luo*, L Wang*, Y Xie*, H Yuan*, S Gui*, H Yu*, Z Xu, J Zhang, ... Journal of Machine Learning Research 22 (240), 1-9, 2021 | 80* | 2021 |
Advanced graph and sequence neural networks for molecular property prediction and drug discovery Z Wang*, M Liu*, Y Luo*, Z Xu*, Y Xie*, L Wang*, L Cai*, Q Qi, Z Yuan, ... Bioinformatics, 2022 | 58* | 2022 |
GOOD: A Graph Out-of-Distribution Benchmark S Gui*, X Li*, L Wang, S Ji NeurIPS 2022 Track on Datasets and Benchmarks, 2022 | 21 | 2022 |
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs L Wang*, Y Liu*, Y Lin, H Liu, S Ji NeurIPS, 2022 | 19 | 2022 |
Learning Hierarchical Protein Representations via Complete 3D Graph Networks L Wang*, H Liu*, Y Liu*, J Kurtin, S Ji International Conference on Learning Representations, 2023 | 12* | 2023 |
GraphFM: Improving Large-Scale GNN Training via Feature Momentum H Yu*, L Wang*, B Wang*, M Liu, T Yang, S Ji International Conference on Machine Learning, 2022 | 9 | 2022 |
Fast quantum property prediction via deeper 2d and 3d graph networks M Liu*, C Fu*, X Zhang, L Wang, Y Xie, H Yuan, Y Luo, Z Xu, S Xu, S Ji NeurIPS 2021 AI for Science Workshop, 2021 | 7 | 2021 |
Development of Xanthene‐Based Fluorescent Dyes: Machine Learning‐Assisted Prediction vs. TD‐DFT Prediction and Experimental Validation Y Wang*, L Cai*, W Chen, D Wang, S Xu, L Wang, MA Kononov, S Ji, ... Chemistry‐Methods 1 (8), 389-396, 2021 | 5 | 2021 |
A Latent Diffusion Model for Protein Structure Generation C Fu*, K Yan*, L Wang, WY Au, M McThrow, T Komikado, K Maruhashi, ... arXiv preprint arXiv:2305.04120, 2023 | 2 | 2023 |
A new perspective on building efficient and expressive 3D equivariant graph neural networks W Du*, Y Du*, L Wang*, D Feng, G Wang, S Ji, C Gomes, ZM Ma arXiv preprint arXiv:2304.04757, 2023 | 2 | 2023 |
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ... arXiv preprint arXiv:2307.08423, 2023 | | 2023 |
Frontiers of Graph Neural Networks with DIG S Ji, M Liu, Y Liu, Y Luo, L Wang, Y Xie, Z Xu, H Yu Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | | 2022 |