DiffEqBase.jl
SciMLTutorials.jl
| DiffEqBase.jl | SciMLTutorials.jl | |
|---|---|---|
| 1 | 1 | |
| 297 | 709 | |
| 1.0% | 0.6% | |
| 9.3 | 1.5 | |
| 3 days ago | 7 days ago | |
| Julia | CSS | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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DiffEqBase.jl
SciMLTutorials.jl
What are some alternatives?
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SciMLBenchmarks.jl - Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
diffeqpy - Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
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]
ComponentArrays.jl - Arrays with arbitrarily nested named components.
DiffEqOperators.jl - Linear operators for discretizations of differential equations and scientific machine learning (SciML)
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)
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StochasticDiffEq.jl - Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem