Physics-Informed Machine Learning Under Small-Data Constraints: Lessons from Abrasive Waterjet Milling

In physically dominated machining processes, experimental datasets are small, expensive, and material-specific; in this regime, data curation, evaluation design, and the form of physics integration can matter as much as the learning algorithm. Using an abrasive waterjet milling dataset ($n{=}155$, I