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ORCIDBin Shao 0002
Person information
- affiliation: Microsoft Research AI4Science, Beijing, China
Other persons with the same name
- Bin Shao — disambiguation page
- Bin Shao 0001
![[0000-0003-1567-9522]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0003-1567-9522")
— Beijing Institute of Technology, Beijing, China - Bin Shao 0003 — Zhejiang University, Hangzhou, Zhejiang, China
- Bin Shao 0004 — Broad Institute Klarman Cell Observatory, Cambridge, MA, USA
- Bin Shao 0005 — China Academy of Space Technology, Xi'an, Shaanxi, China
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2020 – today
- 2026
[i14]Xinran Wei, Yan Pan, Fusong Ju, Zehao Zhou, Yihong Zhang, Lin Huang, Jianwei Zhu, Jia Zhang, Huanhuan Xia, Bin Shao, Tao Qin:
Accelerating Locality-Driven Integration in Quantum Chemistry with Block-Structured Matrix Multiplication. CoRR abs/2605.10363 (2026)- 2025
- [j11]Hongfei Wu, Lijun Wu, Guoqing Liu, Zhirong Liu, Bin Shao, Zun Wang:
SE3Set: Harnessing Equivariant Hypergraph Neural Networks for Molecular Representation Learning. Trans. Mach. Learn. Res. 2025 (2025) - [c15]Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Samuel Harshe, Han Yang, Erpai Luo, Zun Wang, Jia Zhang, Chang Liu, Bin Shao, Mark Gerstein:
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems. ICLR 2025 - [c14]Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang, Zaishuo Xia, Zun Wang, Chang Liu, Bin Shao, Jia Zhang:
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity. ICML 2025 - [i13]Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Han Yang, Sam Harshe, Zun Wang, Chang Liu, Jia Zhang, Bin Shao, Mark B. Gerstein:
Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems. CoRR abs/2502.19227 (2025) - 2024
- [j10]He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao:
Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning. Nat. Comput. Sci. 4(3): 210-223 (2024) - [c13]Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu:
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation. ICLR 2024 - [c12]He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu:
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction. ICML 2024: 59329-59357 - [c11]Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, Nanning Zheng:
Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs. NeurIPS 2024 - [c10]Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao:
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models. NeurIPS 2024 - [i12]He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu:
Self-Consistency Training for Hamiltonian Prediction. CoRR abs/2403.09560 (2024) - [i11]Shaoning Li, Yusong Wang, Mingyu Li, Jian Zhang, Bin Shao, Nanning Zheng, Jian Tang:
F3low: Frame-to-Frame Coarse-grained Molecular Dynamics with SE(3) Guided Flow Matching. CoRR abs/2405.00751 (2024) - [i10]Hongfei Wu, Lijun Wu, Guoqing Liu, Zhirong Liu, Bin Shao, Zun Wang:
SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning. CoRR abs/2405.16511 (2024) - [i9]Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao:
Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models. CoRR abs/2406.03794 (2024) - [i8]Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, Nanning Zheng:
Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs. CoRR abs/2409.17622 (2024) - 2023
- [j9]Zimeng Li, Shichao Zhu, Bin Shao, Xiangxiang Zeng, Tong Wang, Tie-Yan Liu:
DSN-DDI: an accurate and generalized framework for drug-drug interaction prediction by dual-view representation learning. Briefings Bioinform. 24(1) (2023) - [c9]Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Geometric Transformer with Interatomic Positional Encoding. NeurIPS 2023 - [c8]Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao:
Efficiently incorporating quintuple interactions into geometric deep learning force fields. NeurIPS 2023 - [i7]He Zhang, Siyuan Liu, Jiacheng You, Chang Liu, Shuxin Zheng, Ziheng Lu, Tong Wang, Nanning Zheng, Bin Shao:
M-OFDFT: Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning. CoRR abs/2309.16578 (2023) - 2022
- [j8]Siyuan Liu, Yusong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu, Tong Wang:
Improved drug-target interaction prediction with intermolecular graph transformer. Briefings Bioinform. 23(5) (2022) - [j7]Liang He, Bin Shao, Yanghua Xiao, Yatao Li, Tie-Yan Liu, Enhong Chen, Huanhuan Xia:
Neurally-Guided Semantic Navigation in Knowledge Graph. IEEE Trans. Big Data 8(3): 607-615 (2022) - [c7]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu:
SE(3) Equivariant Graph Neural Networks with Complete Local Frames. ICML 2022: 5583-5608 - [i6]Zimeng Li, Shichao Zhu, Bin Shao, Tie-Yan Liu, Xiangxiang Zeng, Tong Wang:
Multi-View Substructure Learning for Drug-Drug Interaction Prediction. CoRR abs/2203.14513 (2022) - [i5]Yusong Wang, Shaoning Li, Tong Wang, Zun Wang, Xinheng He, Bin Shao, Tie-Yan Liu:
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022. CoRR abs/2211.12791 (2022) - 2021
- [j6]Wenze Ding, Qijiang Xu, Siyuan Liu, Tong Wang, Bin Shao, Haipeng Gong, Tie-Yan Liu:
SAMF: a self-adaptive protein modeling framework. Bioinform. 37(22): 4075-4082 (2021) - [j5]Siyuan Liu, Tong Wang, Qijiang Xu, Bin Shao, Jian Yin, Tie-Yan Liu:
Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction. BMC Bioinform. 22(1): 351 (2021) - [c6]He Zhang, Fusong Ju, Jianwei Zhu, Liang He, Bin Shao, Nanning Zheng, Tie-Yan Liu:
Co-evolution Transformer for Protein Contact Prediction. NeurIPS 2021: 14252-14263 - [i4]Siyuan Liu, Yusong Wang, Tong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu:
Improved Drug-target Interaction Prediction with Intermolecular Graph Transformer. CoRR abs/2110.07347 (2021) - [i3]Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu:
Equivariant vector field network for many-body system modeling. CoRR abs/2110.14811 (2021) - [i2]Liang He, Shizhuo Zhang, Lijun Wu, Huanhuan Xia, Fusong Ju, He Zhang, Siyuan Liu, Yingce Xia, Jianwei Zhu, Pan Deng, Bin Shao, Tao Qin, Tie-Yan Liu:
Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model. CoRR abs/2110.15527 (2021) - 2020
- [c5]Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu:
SEEK: Segmented Embedding of Knowledge Graphs. ACL 2020: 3888-3897 - [c4]Jingping Liu, Yanghua Xiao, Ao Wang, Liang He, Bin Shao:
CapableOf Reasoning: A Step Towards Commonsense Oracle. SIGIR 2020: 1797-1800 - [i1]Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu:
SEEK: Segmented Embedding of Knowledge Graphs. CoRR abs/2005.00856 (2020)
2010 – 2019
- 2017
- [j4]Yanghua Xiao, Bin Shao:
Billion-Node Graph Challenges. IEEE Data Eng. Bull. 40(3): 89-99 (2017) - [j3]Liang He, Bin Shao, Yatao Li, Huanhuan Xia, Yanghua Xiao, Enhong Chen, Liang Chen:
Stylus: A Strongly-Typed Store for Serving Massive RDF Data. Proc. VLDB Endow. 11(2): 203-216 (2017) - 2016
- [j2]Hongbin Ma, Bin Shao, Yanghua Xiao, Liang Jeff Chen, Haixun Wang:
G-SQL: Fast Query Processing via Graph Exploration. Proc. VLDB Endow. 9(12): 900-911 (2016) - 2015
- [c3]Liang He, Bin Shao, Yatao Li, Enhong Chen:
Distributed real-time knowledge graph serving. BigComp 2015: 262-265 - 2014
- [c2]Lu Wang, Yanghua Xiao, Bin Shao, Haixun Wang:
How to partition a billion-node graph. ICDE 2014: 568-579 - 2013
- [j1]Zichao Qi, Yanghua Xiao, Bin Shao, Haixun Wang:
Toward a Distance Oracle for Billion-Node Graphs. Proc. VLDB Endow. 7(1): 61-72 (2013) - 2012
- [c1]Bin Shao, Haixun Wang, Yanghua Xiao:
Managing and mining large graphs: systems and implementations. SIGMOD Conference 2012: 589-592
Coauthor Index
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