Symbolic regression using Gram library.
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Updated
May 8, 2017 - C++
Symbolic regression using Gram library.
Package provides C++ implementation of linear genetic programming algorithm
Simple Symbolic Regression
The purpose of the NeuroBase project is finding a way using the neural connectionist approach for handling symbolic paradigm. NeuroBaseLibe is the core library for doing that
Discovering explicit Reynolds-averaged turbulence closures for turbulent separated flows through deep learning-based symbolic regression with non-linear corrections
Genetic Programming version of GOMEA. Also includes standard tree-based GP, and Semantic Backpropagation-based GP
Re-implementation of GP-GOMEA that attempts to be simpler to understand and use than the original.
C++ Large Scale Genetic Programming
Vita - Genetic Programming Framework
Python bindings and scikit-learn interface for the Operon library for symbolic regression.
Evolutionary Algorithms Framework
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