I have recently started using Flux to construct a physics informed neural network. To do this, I start with a model u = Chain(Dense(1, 10), Dense(10,15), Dense(15,1)) Then I construct a function to impose the differential condition y’(t) - y(t) = 0 function f(t) y = sum(u(t)) dy = gradient(() …

Using Flux for a neural net solution to differential equations

ChrisRackauckas June 25, 2020, 2:55am 4

Look at NeuralNetDiffEq.jl which is a repo of physics-informed neural network implementations and deep BSDE methods.

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Gradient error in Flux model inputs