FePySR uses a neural network to pre-extract valid features before PySR search, recovering more equations than baselines on benchmarks and identifying governing ODEs in 24 of 100 biological cases where PySR finds none.
AI feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
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FePySR: A Neural Feature Extraction Framework for Efficient and Scalable Symbolic Regression
FePySR uses a neural network to pre-extract valid features before PySR search, recovering more equations than baselines on benchmarks and identifying governing ODEs in 24 of 100 biological cases where PySR finds none.