BifurcationKit.jl
DiffEqBase.jl
| BifurcationKit.jl | DiffEqBase.jl | |
|---|---|---|
| 1 | 1 | |
| 285 | 298 | |
| 1.1% | 1.3% | |
| 9.4 | 9.3 | |
| 27 days ago | 8 days ago | |
| Julia | Julia | |
| MIT | GNU General Public License v3.0 or later |
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BifurcationKit.jl
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auto-07p VS BifurcationKit.jl - a user suggested alternative
2 projects | 11 Feb 2024
A Julia alternative with methods for automatic bifurcation diagrams. I can work for very large systems.
DiffEqBase.jl
What are some alternatives?
auto-07p - AUTO is a publicly available software for continuation and bifurcation problems in ordinary differential equations originally written in 1980 and widely used in the dynamical systems community.
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.
diffeqpy - Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
ComponentArrays.jl - Arrays with arbitrarily nested named components.
OrdinaryDiffEq.jl - High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
SciMLTutorials.jl - Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
18S096SciML - 18.S096 - Applications of Scientific Machine Learning
StochasticDiffEq.jl - Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
JFVM.jl - A simple finite volume tool for Julia
DiffEqGPU.jl - GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
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