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Chemistry Guided Molecular Graph Transformer
Peisong Niu · Tian Zhou · Qingsong Wen · Liang Sun · Tao Yao
Event URL: https://openreview.net/forum?id=Us3TminqU8v »

Classic methods to calculate molecular properties are insufficient for large amounts of data. The Transformer architecture has achieved competitive performance on graph-level prediction by introducing general graphic embedding. However, the direct spatial encoding strategy ignores important inductive bias for molecular graphs, such as aromaticity and interatomic forces. In this paper, inspired by the intrinsic properties of chemical molecules, we propose a chemistry-guided molecular graph Transformer. Specifically, motif-based spatial embedding and distance-guided multi-scale self-attention for graph Transformer are proposed to predict molecular property effectively. To evaluate the proposed methods, we have conducted experiments on two large molecular property prediction datasets, ZINC, and PCQM4M-LSC. The results show that our methods achieve superior performance compared to various state-of-the-art methods.Code is available at https://github.com/PSacfc/chemistry-graph-transformer .

Author Information

Peisong Niu
Tian Zhou (Alibaba Group)
Qingsong Wen (Alibaba Group U.S. Inc.)

Dr. Qingsong Wen is a Staff Engineer / Team Leader at DAMO Academy-Decision Intelligence Lab, Alibaba Group (U.S.), working in the areas of intelligent time series analysis, data-driven intelligence decisions, machine learning, and signal processing. He received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology, Atlanta, USA. He has published over 40 top-ranked conference and journal papers, and won First Place in the 2022 ICASSP Grand Challenge (AIOps in Networks) Competition. He is an Associate Editor for Neurocomputing, Guest Editor for Pattern Recognition, Guest Editor for Applied Energy, and regularly served as an SPC/PC member of the major DM/ML/AI conferences including KDD, ICDM, AAAI, IJCAI, etc.

Liang Sun (Alibaba Group)
Tao Yao (Alibaba Group)

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