Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

Documenti analoghi

• Machine Learning-Driven Crystal System Prediction for Perovskites Using Augmented X-ray Diffraction Data
  di: Mathew, Ansu, et al.
  Pubblicazione: (2026)
• A Data-Driven Machine Learning Approach for Predicting Axial Load Capacity in Steel Storage Rack Columns
  di: Mammadli, Bakhtiyar, et al.
  Pubblicazione: (2025)
• Physics-Informed Machine Learning for Steel Development: A Computational Framework and CCT Diagram Modelling
  di: Hedström, Peter, et al.
  Pubblicazione: (2025)
• On-Demand Growth of Semiconductor Heterostructures Guided by Physics-Informed Machine Learning
  di: Shen, Chao, et al.
  Pubblicazione: (2024)
• Predicting and Accelerating Nanomaterials Synthesis Using Machine Learning Featurization
  di: Price, Christopher C., et al.
  Pubblicazione: (2024)