PET-UAFD ensemble of ML potentials, calibrated on experimental cohesive energies and moduli, matches experimental accuracy on liquid properties and supplies uncertainty estimates via the PET-EXP protocol.
Pernot, The long road to calibrated prediction uncer- tainty in computational chemistry, The Journal of Chem- ical Physics156, 114109 (2022)
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Errors that matter: Uncertainty-aware universal machine-learning potentials calibrated on experiments
PET-UAFD ensemble of ML potentials, calibrated on experimental cohesive energies and moduli, matches experimental accuracy on liquid properties and supplies uncertainty estimates via the PET-EXP protocol.