arXiv stat.ML
· Papers
Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation
arXiv:2605.10378v2 Announce Type: replace Abstract: Reliable uncertainty quantification is essential for the use of machine learning in physics, where scientific discoveries depend on validated probabilistic statements. We provide a structured overview of uncertainty quantification in ML for physics, introducing a unif