Genetic Programming in Python, with a scikit-learn inspired API
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Updated
Nov 29, 2023 - Python
Genetic Programming in Python, with a scikit-learn inspired API
Physical Symbolic Optimization
High-Performance Symbolic Regression in Python and Julia
Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning.
A framework for gene expression programming (an evolutionary algorithm) in Python
A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.
Distributed High-Performance Symbolic Regression in Julia
Symbolic regression solver, based on genetic programming methodology.
C++ Large Scale Genetic Programming
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
Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"
EC-KitY is a scikit-learn-compatible Python tool kit for doing evolutionary computation.
a python 3 library based on deap providing abstraction layers for symbolic regression problems.
Simple Genetic Programming for Symbolic Regression in Python3
HeuristicLab - An environment for heuristic and evolutionary optimization
Automatic equation building and curve fitting. Runs on Tensorflow. Built for academia and research.
SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
Ridiculously fast symbolic expressions
Python bindings and scikit-learn interface for the Operon library for symbolic regression.
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