There are 24 repositories under symbolic-regression topic.
Physical Symbolic Optimization
High-Performance Symbolic Regression in Python and Julia
Genetic Programming in Python, with a scikit-learn inspired API
Distributed High-Performance Symbolic Regression in Julia
A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.
Symbolic regression solver, based on genetic programming methodology.
C++ Large Scale Genetic Programming
SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
Ridiculously fast symbolic expressions
Automatic equation building and curve fitting. Runs on Tensorflow. Built for academia and research.
Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"
:crystal_ball: Symbolic regression library
predicting equations from raw data with deep learning
Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.
Genetic Programming version of GOMEA. Also includes standard tree-based GP, and Semantic Backpropagation-based GP
Symbolic regression is the task of identifying a mathematical expression that best fits a provided dataset of input and output values. In this work, we present SymbolicGPT, a novel transformer-based language model for symbolic regression.
[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"
AI Physicist, a paradigm with algorithms for learning theories from data, by Wu and Tegmark (2019)
HeuristicLab - An environment for heuristic and evolutionary optimization
Python bindings and scikit-learn interface for the Operon library for symbolic regression.
[ICLR 2024 Spotlight] This is the official code for the paper "SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training"
Cartesian genetic programming (CGP) in pure Python.
Simple Genetic Programming for Symbolic Regression in Python3
A baseline implementation of genetic programming (using trees to encode programs) with some examples of usage.
[DMLR] Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery
Code for the GP-RC algorithm presented in "Genetic Programming with Rademacher Complexity for Symbolic Regression" (CEC-2019). Paper Link: https://ieeexplore.ieee.org/document/8790341
📜 [Under Review] "Symbolic Visual Reinforcement Learning: A Scalable Framework with Object-Level Abstraction and Differentiable Expression Search", Wenqing Zheng*, S P Sharan*, Zhiwen Fan, Kevin Wang, Yihan Xi, Atlas Wang