Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials

Documenti analoghi

• Efficient Grand Canonical Global Optimization with On-the-fly-trained Machine-learning Interatomic Potentials
  di: Dominguez, Jon Eunan Quinlivan, et al.
  Pubblicazione: (2025)
• Comparing the latent features of universal machine-learning interatomic potentials
  di: Chorna, Sofiia, et al.
  Pubblicazione: (2025)
• Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials
  di: Nam, Juno, et al.
  Pubblicazione: (2024)
• How accurate are foundational machine learning interatomic potentials for heterogeneous catalysis?
  di: Kempen, Luuk H. E., et al.
  Pubblicazione: (2025)
• Unifying the description of hydrocarbons and hydrogenated carbon materials with a chemically reactive machine learning interatomic potential
  di: Ibragimova, Rina, et al.
  Pubblicazione: (2024)