Deep symbolic regression for physics guided by units constraints: toward the automated discovery of physical laws

1 code implementation • 6 Mar 2023 • Wassim Tenachi, Rodrigo Ibata, Foivos I. Diakogiannis

Here we present $\Phi$-SO, a Physical Symbolic Optimization framework for recovering analytical symbolic expressions from physics data using deep reinforcement learning techniques by learning units constraints.

Symbolic Regression