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
SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals
Automatic equation building and curve fitting. Runs on Tensorflow. Built for academia and research.
Cartesian genetic programming (CGP) in pure Python.
predicting equations from raw data with deep learning
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