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DiffEqFlux.jl
  • DiffEqFlux.jl: Generalized Physics-Informed and Scientific Machine Learning (SciML)
  • Ordinary Differential Equation (ODE) Tutorials
    • Optimization of Ordinary Differential Equations
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    • Continuous Normalizing Flows with GalacticOptim.jl
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    • Neural Ordinary Differential Equations with GalacticOptim.jl
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  • Training Techniques
    • Multiple Shooting
    • Strategies to Avoid Local Minima
    • Prediction error method (PEM)
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    • Neural Jump Diffusions (Neural Jump SDE) and Neural Partial Differential Equations (Neural PDEs)
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    • Bayesian Estimation of Differential Equations with Probabilistic Programming
    • Bayesian Neural ODEs: NUTS
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    • Physics Informed Machine Learning with TensorLayer
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  • Bayesian Estimation Tutorials
  • Bayesian Estimation of Differential Equations with Probabilistic Programming
  • Bayesian Estimation of Differential Equations with Probabilistic Programming
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Bayesian Estimation of Differential Equations with Probabilistic Programming

For a good overview of how to use the tools of SciML in conjunction with the Turing.jl probabilistic programming language, see the Bayesian Differential Equation Tutorial.

« Neural Jump Diffusions (Neural Jump SDE) and Neural Partial Differential Equations (Neural PDEs)Bayesian Neural ODEs: NUTS »

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