SciML Open Source Scientific Machine Learning
Websites:Organization Website |Documentation
SciML Organization Stats:
The SciML organization is a collection of tools for solving equations and modeling systemsdeveloped in the Julia programming language with bindings to other languages such as R andPython. The organization provides well-maintained tools which compose together as acoherent ecosystem. It has a coherent development principle, unified APIs over largecollections of equation solvers, pervasive differentiability and sensitivity analysis, andfeatures many of the highest performance and parallel implementations one can find.
Scientific Machine Learning (SciML) = Scientific Computing + Machine Learning
- Want to get started running some code? Check out theGetting Started tutorials.
- What is SciML? Check out ourOverview.
- Want to see some cool end-to-end examples? Check out theSciML Showcase.
- Want to learn more about how SciML does scientific machine learning? Check out theSciML Book (from MIT's 18.337 graduate course).
- Curious about our performance claims? Check outthe SciML Open Benchmarks.
- Want to chat with someone? Check outour chat room andforums.
- Want to see our code? Check outthe SciML Github organization.
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- DifferentialEquations.jl
DifferentialEquations.jl PublicMulti-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equat…
- ModelingToolkit.jl
ModelingToolkit.jl PublicAn acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning a…
- NeuralPDE.jl
NeuralPDE.jl PublicPhysics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
- DiffEqFlux.jl
DiffEqFlux.jl PublicPre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Repositories
- DiffEqDocs.jl Public
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
SciML/DiffEqDocs.jl’s past year of commit activity - SciMLSensitivity.jl Public
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.
SciML/SciMLSensitivity.jl’s past year of commit activity - DiffEqDevTools.jl Public
Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
SciML/DiffEqDevTools.jl’s past year of commit activity - OrdinaryDiffEq.jl Public
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
SciML/OrdinaryDiffEq.jl’s past year of commit activity - StructuralIdentifiability.jl Public
Fast and automatic structural identifiability software for ODE systems
SciML/StructuralIdentifiability.jl’s past year of commit activity - ModelingToolkit.jl Public
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
SciML/ModelingToolkit.jl’s past year of commit activity - ModelingToolkitStandardLibrary.jl Public
A standard library of components to model the world and beyond
SciML/ModelingToolkitStandardLibrary.jl’s past year of commit activity