Showing 1 open source project for "automatic differentiation"

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    StructuralEquationModels.jl

    StructuralEquationModels.jl

    A fast and flexible Structural Equation Modelling Framework

    ...We provide fast objective functions, gradients, and for some cases hessians as well as approximations thereof. As a user, you can easily define custom loss functions. For those, you can decide to provide analytical gradients or use finite difference approximation / automatic differentiation. You can choose to mix loss functions natively found in this package and those you provide. In such cases, you optimize over a sum of different objectives (e.g. ML + Ridge). This strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mixed analytical and automatic differentiation. ...
    Downloads: 1 This Week
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