Local surrogate models for harmonic vibrational entropy in multilattices achieve linear scaling with sublattice-resolved locality proofs and controlled truncation error on finite-range models.
Fine-tuning universal machine-learned interatomicpotentials: Atutorialonmethodsandapplications
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Distilled compact MLIPs from transfer-learned teachers reproduce observables more reliably than same-size models trained directly and enable practical PIMD umbrella sampling of water dissociation at TiO2 interface with NQE effects matching NMR.
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Local Surrogates for Harmonic Vibrational Entropy in Multilattices
Local surrogate models for harmonic vibrational entropy in multilattices achieve linear scaling with sublattice-resolved locality proofs and controlled truncation error on finite-range models.
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Distilling first-principles accuracy into compact machine learning potentials for condensed-phase chemistry
Distilled compact MLIPs from transfer-learned teachers reproduce observables more reliably than same-size models trained directly and enable practical PIMD umbrella sampling of water dissociation at TiO2 interface with NQE effects matching NMR.