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DifferentialEquations.jl
  • DifferentialEquations.jl: Scientific Machine Learning (SciML) Enabled Simulation and Estimation
  • Tutorials
    • Ordinary Differential Equations
    • Code Optimization for Differential Equations
    • Solving Large Stiff Equations
    • Stochastic Differential Equations
    • Random Ordinary Differential Equations
    • Delay Differential Equations
    • Differential Algebraic Equations
    • Continuous-Time Jump Processes and Gillespie Methods
    • Jump Diffusion Equations
    • Boundary Value Problems
    • Additional Tutorials
  • Basics
    • Overview of DifferentialEquations.jl
    • Common Solver Options
    • Solution Handling
    • Plot Functions
    • Integrator Interface
    • Problem Interface
    • Frequently Asked Questions
    • Solver Compatibility Chart
  • Problem Types
    • Discrete Problems
    • ODE Problems
    • Non-autonomous Linear ODE / Lie Group Problems
    • Dynamical, Hamiltonian and 2nd Order ODE Problems
    • Split ODE Problems
    • Steady State Problems
    • BVP Problems
    • SDE Problems
    • SDAE Problems
    • RODE Problems
    • DDE Problems
    • SDDE Problems
    • DAE Problems
    • Jump Problems
  • Solver Algorithms
    • Discrete Solvers
    • ODE Solvers
    • Non-autonomous Linear ODE / Lie Group ODE Solvers
    • Dynamical, Hamiltonian, and 2nd Order ODE Solvers
    • Split ODE Solvers
    • Steady State Solvers
    • BVP Solvers
    • Jump Problem and Jump Diffusion Solvers
    • SDE Solvers
    • SDAE Solvers
    • RODE Solvers
    • DDE Solvers
    • SDDE Solvers
    • DAE Solvers
    • Solver Benchmarks
  • Additional Features
    • Jacobians, Gradients, etc.
    • DiffEq-Specific Array Types
    • DiffEqOperators
    • Noise Processes
    • Specifying (Non)Linear Solvers and Preconditioners
    • Event Handling and Callback Functions
    • Callback Library
    • Parallel Ensemble Simulations
    • I/O: Saving and Loading Solution Data
    • Low Dependency Usage
    • Progress Bar Integration
  • Analysis Tools
    • ParameterizedFunctions
    • Parameter Estimation and Bayesian Analysis
    • Bifurcation Analysis
    • Local Sensitivity Analysis (Automatic Differentiation)
    • Global Sensitivity Analysis
    • Uncertainty Quantification
    • Neural Networks
    • Algorithm Development and Testing
  • Domain Modeling Tools
    • Multi-Scale Models
    • Physical Models
    • Financial Models
    • Chemical Reactions
    • External Modeling Packages
  • Extra Details
    • Timestepping Method Descriptions
    • Mathematics of Sensitivity Analysis
Version
  • Analysis Tools
  • Neural Networks
  • Neural Networks
Edit on GitHub

Neural Networks

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

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