SimpleDiffEq.jl
Simple differential equation solvers in native Julia for scientific machine learning (SciML) (by SciML)
QMUL
Repository of code and notes for the MSc. in Maths at Queen Mary University of London (by gerdm)
SimpleDiffEq.jl | QMUL | |
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1 | 1 | |
22 | 4 | |
- | - | |
5.9 | 0.0 | |
6 days ago | almost 3 years ago | |
Julia | Jupyter Notebook | |
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.
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.
SimpleDiffEq.jl
Posts with mentions or reviews of SimpleDiffEq.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-27.
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Tutorials for Learning Runge-Kutta Methods with Julia?
There you go, that's one step of it, taken from SimpleDiffEq.jl. But that's a really bad method and should almost never be used in practice.
QMUL
Posts with mentions or reviews of QMUL.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-27.
What are some alternatives?
When comparing SimpleDiffEq.jl and QMUL you can also consider the following projects:
DiffEqDevTools.jl - Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
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