Simulation as Supervision: Mechanistic Pretraining for Scientific Discovery

ArXi:2507.08977v4 Announce Type: replace-cross Scientific modeling faces a tradeoff between the interpretability of mechanistic theory and the predictive power of machine learning. While existing hybrid approaches have made progress by incorporating domain knowledge into machine learning methods as functional constraints, they can be limited by a reliance on precise mathematical specifications.