159 citations · 457 across the 18 of their papers we have counts for
3 papers · 1 filter
A unified framework for machine learning collective variables for enhanced sampling simulations:
Luigi Bonati, Enrico Trizio, Andrea Rizzi +1
Identifying a reduced set of collective variables is critical for understanding atomistic simulations and accelerating them through enhanced sampling techniques. Recently, several…
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
John Falk, Luigi Bonati, Pietro Novelli +2
Interatomic potentials learned using machine learning methods have been successfully applied to atomistic simulations. However, accurate models require large training datasets, whi…
Unraveling the Crystallization Kinetics of the GeSbTe Phase Change Compound with a Machine-Learned Interatomic Potential
Omar Abou El Kheir, Luigi Bonati, Michele Parrinello +1
The phase change compound GeSbTe (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible…