High-Performance Symbolic Regression in Python and Julia
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Updated
Aug 2, 2024 - Python
High-Performance Symbolic Regression in Python and Julia
This is a Python library that implements a Multi-objective Symbolic Regression algorithm. It can be used as a Machine Learning algorithm to create predictive models in the form of mathematical expressions.
A baseline implementation of genetic programming (using trees to encode programs) with some examples of usage.
Physical Symbolic Optimization
EC-KitY is a scikit-learn-compatible Python tool kit for doing evolutionary computation.
Using deep symbolic regression for the discovery of a causal relationship between Williams coefficients and crack tip position using PhySO
Official code implementation for the ACL 2024 Student Research Workshop paper "In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery"
Symbolic Regression with Univariate Skeleton Prediction in Multivariate Systems Using Transformers
Official implementation of CoNSAL for analytical Lyapunov function discovery
Evolving Symbolic Pruning Metric from scratch
[ICLR 2024 Spotlight] SNIP on Symbolic Regression: Deep Symbolic Regression with Multimodal Pretraining
[ICLR 2024 Spotlight] This is the official code for the paper "SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training"
Machine learning library for symbolic fitting: the unknown system/function is described via NARMAX algebraic expressions being linear combinations of arbitrary non-linear terms provided by the user (like 0.2x²+0.7sin(x) or x[k-1]*y[k-4]^2).
Symbolic regression of physical models via Genetic Programming.
Extremly fast c++/python symbolic regression library based on parallel local search.
Cartesian genetic programming (CGP) in pure Python.
end-to-end implementation of symbolic regression with expression trees and genetic optimization algorithm.
[DMLR] Rethinking Symbolic Regression Datasets and Benchmarks for Scientific Discovery
Using Genetic programming, an Evolutionary Algorithm, to solve and research the problem of Symbolic regression analysis and Rice Classification.
A simple tree-based Genetic Programming for symbolic regression in Python
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