Bayesian symbolic regression, using the posterior over formulas and explicit priors, is presented as the principled foundation for equation discovery, while heuristic symbolic regression is shown to overfit even constant data.
2007 Computational Discovery of Scientific Knowledge
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Bayesian symbolic regression: Automated equation discovery from a physicists' perspective
Bayesian symbolic regression, using the posterior over formulas and explicit priors, is presented as the principled foundation for equation discovery, while heuristic symbolic regression is shown to overfit even constant data.