2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
NeurIPS 2020oral
We present an improved method for symbolic regression that seeks to fit data to formulas that are Pareto-optimal, in the sense of having the best accuracy for a given complexity. It improves on the previous state-of-the-art by typically being orders of magnitude more robust toward noise and bad data…