FB-GNN-MBE integrates fragment-based graph neural networks into many-body expansion to predict two- and three-body energies for water, phenol, and mixture systems at chemical accuracy, with a teacher-student protocol enabling transfer to new cluster sizes without full retraining.
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Transferable FB-GNN-MBE Framework for Potential Energy Surfaces: Data-Adaptive Transfer Learning in Deep Learned Many-Body Expansion Theory
FB-GNN-MBE integrates fragment-based graph neural networks into many-body expansion to predict two- and three-body energies for water, phenol, and mixture systems at chemical accuracy, with a teacher-student protocol enabling transfer to new cluster sizes without full retraining.