Quadruple Attention in Many-body Systems for Accurate Molecular Property Predictions
Published in International Conference on Machine Learning(ICML), 2025
MABNet introduces a geometric attention framework that efficiently models four-body atomic interactions, overcoming limitations of traditional methods in capturing complex many-body effects, and achieves state-of-the-art performance on molecular property prediction benchmarks.