Abstract: genetic programming (GP) is a widely recognized and powerful approach for symbolic regression (SR) problems. However, existing GP methods rely on a single form to solve the problem, which ...
This repository contains the code and data for the experiments in the paper "Discovering network dynamics with neural symbolic regression", published in Nature Computational Science (2025). Abstract: ...
Abstract: Physics-informed symbolic regression aims to recover explicit closed-form solutions of differential equations while preserving physical consistency. However, existing methods often suffer ...
FunctionEvolve is a neuro-symbolic evolutionary framework for scientific equation discovery. It combines LLM reasoning with an explicit abstract-syntax-tree (AST) search: domain-informed seeds and ...
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