AIBullisharXiv – CS AI · Mar 37/107
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Enhancing Molecular Property Predictions by Learning from Bond Modelling and Interactions
Researchers introduce DeMol, a new dual-graph framework for molecular property prediction that explicitly models both atoms and chemical bonds to achieve superior accuracy. The approach addresses limitations of conventional atom-centric models by incorporating bond-level phenomena like resonance and stereoselectivity, establishing new state-of-the-art results across multiple benchmarks.
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