פריטים דומים

• When Active Learning Fails, Uncalibrated Out of Distribution Uncertainty Quantification Might Be the Problem
  מאת: Dale, Ashley S., et al.
  יצא לאור: (2025)
• Efficient first principles based modeling via machine learning: from simple representations to high entropy materials
  מאת: Li, Kangming, et al.
  יצא לאור: (2024)
• Reproducibility in Computational Materials Science: Lessons from 'A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials'
  מאת: Persaud, Daniel, et al.
  יצא לאור: (2023)
• Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scores
  מאת: Amirian, Benhour, et al.
  יצא לאור: (2025)
• Probing out-of-distribution generalization in machine learning for materials
  מאת: Li, Kangming, et al.
  יצא לאור: (2024)