Gradient-based grand canonical optimization enabled by graph neural networks with fractional atomic existence

Documenti analoghi

• $Δ$-model correction of Foundation Model based on the models own understanding
  di: Christiansen, Mads-Peter Verner, et al.
  Pubblicazione: (2025)
• Active Δ-learning with universal potentials for global structure optimization
  di: Pitfield, Joe, et al.
  Pubblicazione: (2025)
• Cascading symmetry constraint during machine learning-enabled structural search for sulfur induced Cu(111)-$(\sqrt{43}\times\sqrt{43})$ surface reconstruction
  di: Brix, Florian, et al.
  Pubblicazione: (2025)
• Augmentation of Universal Potentials for Broad Applications
  di: Pitfield, Joe, et al.
  Pubblicazione: (2024)
• Advancing atomic electron tomography with neural networks
  di: Lee, Juhyeok, et al.
  Pubblicazione: (2025)