stochastica
StochasticDiffEq.jl
| stochastica | StochasticDiffEq.jl | |
|---|---|---|
| 1 | 1 | |
| 4 | 235 | |
| - | 0.9% | |
| 0.0 | 7.8 | |
| about 2 years ago | 7 days ago | |
| HTML | Julia | |
| MIT License | GNU General Public License v3.0 or later |
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stochastica
StochasticDiffEq.jl
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Writing unit tests in scientific computing
For stochastic processes you have to work a little bit more. However maybe the StochasticDiffEq.jl package can give some guiding there https://github.com/SciML/StochasticDiffEq.jl/tree/master/test
What are some alternatives?
torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
SciMLTutorials.jl - Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
DiffEqBase.jl - The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
SciMLSensitivity.jl - A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
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)
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]
DiffEqOperators.jl - Linear operators for discretizations of 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.
Clapeyron.jl - Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC.