SymbolicRegression.jl
SymbolicNumericIntegration.jl
| SymbolicRegression.jl | SymbolicNumericIntegration.jl | |
|---|---|---|
| 3 | 1 | |
| 544 | 113 | |
| - | 0.0% | |
| 9.7 | 7.3 | |
| 10 days ago | 16 days ago | |
| Julia | Julia | |
| Apache License 2.0 | MIT License |
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SymbolicRegression.jl
- Symbolicregression.jl – High-Performance Symbolic Regression in Julia and Python
- Do Simpler Machine Learning Models Exist and How Can We Find Them?
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Modules in Julia
This is an example of a package that relies on it heavily: https://github.com/MilesCranmer/SymbolicRegression.jl
SymbolicNumericIntegration.jl
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[2201.12468] Symbolic-Numeric Integration of Univariate Expressions based on Sparse Regression
The repository associated with this paper is https://github.com/SciML/SymbolicNumericIntegration.jl.
What are some alternatives?
FromFile.jl - Julia enhancement proposal (Julep) for implicit per file module in Julia
MuladdMacro.jl - This package contains a macro for converting expressions to use muladd calls and fused-multiply-add (FMA) operations for high-performance in the SciML scientific machine learning ecosystem
symreg - A Symbolic Regression engine
Catalyst.jl - Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
hlb-CIFAR10 - Train CIFAR-10 in <7 seconds on an A100, the current world record.
DataDrivenDiffEq.jl - Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
Metatheory.jl - Makes Julia reason with equations. General purpose metaprogramming, symbolic computation and algebraic equational reasoning library for the Julia programming language: E-Graphs & equality saturation, term rewriting and more.
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
DifferentialEquations.jl - Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
PySR - High-Performance Symbolic Regression in Python and Julia
Optimization.jl - Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.