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20232026
most citedEfficiency, Accuracy, and Transferability of Machine Learning Potentials: Application to Dislocations and Cracks in Iron

38 citations · 59 across the 10 of their papers we have counts for

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physics.chem-ph2024

Random Spin Committee Approach For Smooth Interatomic Potentials

Vlad Cărare, Volker L. Deringer, Gábor Csányi

Training interatomic potentials for spin-polarized systems continues to be a difficult task for the molecular modeling community. In this note, a proof-of-concept, random initial s…

physics.chem-ph2024★ 5 cited

Transferability of datasets between Machine-Learning Interaction Potentials

Samuel P. Niblett, Panagiotis Kourtis, Ioan-Bogdan Magdău +2

With the emergence of Foundational Machine Learning Interatomic Potential (FMLIP) models trained on extensive datasets, transferring data between different ML architectures has bec…