DiffEqBase.jl VS SciMLTutorials.jl

Compare DiffEqBase.jl vs SciMLTutorials.jl and see what are their differences.

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DiffEqBase.jl SciMLTutorials.jl
1 1
297 708
3.7% 0.4%
9.3 3.1
12 days ago 8 months ago
Julia CSS
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

DiffEqBase.jl

Posts with mentions or reviews of DiffEqBase.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-29.

SciMLTutorials.jl

Posts with mentions or reviews of SciMLTutorials.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-21.

What are some alternatives?

When comparing DiffEqBase.jl and SciMLTutorials.jl you can also consider the following projects:

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.

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)

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.

18S096SciML - 18.S096 - Applications of Scientific Machine Learning

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