Atom-level Adaptive Receptive Fields: A Pruning-Based Encoder for 2D Molecular Graphs (Student Abstract)

The two-dimensional (2D) graph structure of a molecule encodes abundant latent property information. A well-designed molecular graph encoder can capture informative low-dimensional dense representations of molecules, which can subsequently be applied to a widerange of downstream tasks. To achieve fine-grained anddiscriminative molecular representations that capture localized structural information, we propose an novel atom-level adaptive receptive field encoder, enabling each atomic node in the molecular graph to dynamically adjust its receptive field size. To the best of our knowledge, we are the first to introduce an effective rank-guided pruning strategy for 2D molecular graphs.

Authors

• Yuhao Zhang Northeastern University, China
• Ningkang Peng Nanjing Normal University
• Yafei Liu Nanjing Normal University
• Lin Li Shanxi University
• Masaru Kitsuregawa Institute of Industrial Science, The University of Tokyo
• Yanhui Gu School of Computer and Electronic Information Science, Nanjing Normal University

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