Symbolic regression is a very interpretable machine learning algorithm for low-dimensional problems: these tools search equation space to find algebraic relations that approximate a dataset. One can ...

High-Performance Symbolic Regression in Python and Julia. ... [ICLR 2025 Oral] This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with Large ...

This study proposes a method for solving unsolved mathematical games using symbolic regression libraries. We aimed to demonstrate the effectiveness of genetic programming in mathematics in rendering ...

Symbolic Regression is especially useful in cases where features in a dataset are known to have distinct mathematical relations to each other and its output. Therefore, this paper aims to compare and ...