SciMLTutorials.jl
DiffEqBase.jl
Our great sponsors
SciMLTutorials.jl | DiffEqBase.jl | |
---|---|---|
1 | 1 | |
706 | 295 | |
0.1% | 3.1% | |
3.1 | 9.3 | |
8 months ago | 11 days ago | |
CSS | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SciMLTutorials.jl
DiffEqBase.jl
What are some alternatives?
SciMLBenchmarks.jl - Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
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.
DiffEqSensitivity.jl - A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc. [Moved to: https://github.com/SciML/SciMLSensitivity.jl]
diffeqpy - Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
DiffEqOperators.jl - Linear operators for discretizations of differential equations and scientific machine learning (SciML)
ComponentArrays.jl - Arrays with arbitrarily nested named components.
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.
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)
18337 - 18.337 - Parallel Computing and 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