The SciML Open Souce Software Ecosystem
Equation Solvers
Partial Differential Equation Solvers
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- ModelingToolkit
- ModelingToolkitStandardLibrary
- Catalyst
- NBodySimulator
- ParameterizedFunctions
  - Home
  - The ode_def macro
Inverse Problems
- Parameter Estimation, Bayesian Analysis, and Inverse Problems Overview
- SciMLSensitivity
  - SciMLSensitivity.jl: Automatic Differentiation and Adjoints for (Differential) Equation Solvers
  - Tutorials
    - Differentiating Ordinary Differential Equations (ODE) Tutorials
    - Fitting Ordinary Differential Equation (ODE) Tutorials
    - Training Techniques and Tips
    - Neural Ordinary Differential Equation (Neural ODE) Tutorials
    - Stochastic Differential Equation (SDE) Tutorials
      - Optimization of Stochastic Differential Equations
    - Delay Differential Equation (DDE) Tutorials
      - Delay Differential Equations
    - Differential-Algebraic Equation (DAE) Tutorials
      - Enforcing Physical Constraints via Universal Differential-Algebraic Equations
    - Partial Differential Equation (PDE) Tutorials
      - Partial Differential Equation (PDE) Constrained Optimization
    - Hybrid and Jump Equation Tutorials
      - Training Neural Networks in Hybrid Differential Equations
      - Bouncing Ball Hybrid ODE Optimization
    - Bayesian Estimation Tutorials
      - Bayesian Estimation of Differential Equations with Probabilistic Programming
    - Optimal and Model Predictive Control Tutorials
  - Manual and APIs
  - Benchmarks
  - Sensitivity Math Details
- DiffEqParamEstim
- DiffEqBayes
AbstractArray Libraries
- AbstractArray Libraries
- RecursiveArrayTools
- LabelledArrays
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  - Home
  - API
Uncertainty Quantification
- Uncertainty Quantification Overview
- PolyChaos
Simulation Analysis
- SciML Simulation Analysis Utilities
- GlobalSensitivity
Symbolic Analysis
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- SymbolicNumericIntegration
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  - API
Interfaces
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- SciMLBase
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- CommonSolve
  - The Common Solve Interface
Numerical Utilities
- SciML Numerical Utility Libraries
- Surrogates
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- DiffEqNoiseProcess
- PoissonRandom
  - Home
  - Poisson Random API
- QuasiMonteCarlo
  - Home
  - Sampler APIs
- DataInterpolations
  - DataInterpolations.jl
- FFTW
  - FFTW.jl
- RuntimeGeneratedFunctions
  - RuntimeGeneratedFunctions.jl
- MuladdMacro
  - MuladdMacro.jl
Machine Learning
- SciML Machine Learning Libraries Overview
- DiffEqFlux
Learning Resources
- Curated Learning, Teaching, and Training Resouces
Developer Documentation
- Developer Documentation
- SciMLStyle
  - SciML Style Guide for Julia
- COLPRAC
  - ColPrac: Contributor's Guide on Collaborative Practices for Community Packages
- DiffEq Developer Documentation
  - Home
  - Contributor Guide
  - Algorithm Development Tools
  - Internal Documentation
    - Notes on Algorithms
    - ODE Tableaus

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Equation Solvers
DifferentialEquations
Analysis Tools
Neural Networks

Neural Networks

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Neural Networks

To use DifferentialEquations.jl with the Flux.jl neural network package, consult the documentation at DiffEqFlux.jl.

« Uncertainty Quantification Algorithm Development and Testing »

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