papersSEP 10 04:00 UTC
Physics-Guided Machine Learning Extrapolation Framework Validated on Diffusion Benchmark
A new arXiv paper introduces a physics-guided machine learning framework designed to make reliable predictions outside the limited operating ranges in which engineering models are typically trained. The authors argue that extrapolation, rather than interpolation, is the central challenge for applied ML, and they validate their approach using a classical transient diffusion problem as a benchmark.