10 citations · 10 across the 2 of their papers we have counts for
2 papers
physics.chem-ph2024★ 10 cited
Prediction rigidities for data-driven chemistry
Sanggyu Chong, Filippo Bigi, Federico Grasselli +3
The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures with…
physics.chem-ph2023
Physics-inspired Equivariant Descriptors of Non-bonded Interactions
Kevin K. Huguenin-Dumittan, Philip Loche, Ni Haoran +1
One essential ingredient in many machine learning (ML) based methods for atomistic modeling of materials and molecules is the use of locality. While allowing better system-size sca…