Preprint
Jul 2026
DeepPySR -- A Symbolic Regression Framework with Dynamic Pruning, Pareto Selection, and Hierarchical Composition for Real-World Scientific Discovery
DeepPySR is introduced, which addresses SR's challenges with a dynamic variable-pruning schedule to remove irrelevant features during search, an exponential Pareto selection criterion that eliminates trade-offs between accuracy and complexity, and a multi-layer architecture for hierarchical symbolic composition.
Fuling Chen, K. Vinsen, Phillip E. Melton et al.
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