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.
2023 Fundamental limits to learning closed-form mathematical models from data
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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.