Neural P3M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs Yusong Wang

Geometric graph neural networks (GNNs) have emerged as powerful tools for modeling molecular geometry. However, they encounter limitations in effectively capturing long-range interactions in large molecular systems due to the localization assumption of GNN.