2 citations · 3 across the 2 of their papers we have counts for
2 papers
physics.chem-ph2025★ 1 cited
Generalization of Long-Range Machine Learning Potentials in Complex Chemical Spaces
Michal Sanocki, Julija Zavadlav
The vastness of chemical space makes generalization a central challenge in the development of machine learning interatomic potentials (MLIPs). While MLIPs could enable large-scale…
physics.chem-ph2025★ 2 cited
Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration
Paul Fuchs, Michał Sanocki, Julija Zavadlav
Graph Neural Network (GNN) potentials relying on chemical locality offer near-quantum mechanical accuracy at significantly reduced computational costs. Message-passing GNNs model i…