Machine learning modularity
A transformer-based machine learning framework automatically simplifies complex mathematical expressions involving multiple elliptic Gamma functions by applying algebraic identities like SL(2, Z) and SL(3, Z) modular transformations. The model learns these rules from training data to reduce scrambled expressions to canonical forms with over 99% accuracy.