Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable Targets

Documenti analoghi

• A Straightforward Gradient-Based Approach for High-Tc Superconductor Design: Leveraging Domain Knowledge via Adaptive Constraints
  di: Fujii, Akihiro, et al.
  Pubblicazione: (2024)
• Machine-learning potential for phonon transport in AlN with defects in multiple charge states
  di: Dou, Ying, et al.
  Pubblicazione: (2024)
• MaterialBENCH: Evaluating College-Level Materials Science Problem-Solving Abilities of Large Language Models
  di: Yoshitake, Michiko, et al.
  Pubblicazione: (2024)
• Representing Born effective charges with equivariant graph convolutional neural networks
  di: Kutana, Alex, et al.
  Pubblicazione: (2024)
• CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling
  di: Ito, Yusei, et al.
  Pubblicazione: (2025)