WIP: adds lagrangian nn and simlple example #537
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avik-pal
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Apr 24, 2021
avik-pal
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Apr 24, 2021
avik-pal
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Apr 24, 2021
avik-pal
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Apr 24, 2021
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| # One point test | |||
| using Flux, ReverseDiff, LagrangianNN | |||
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This should be moved to test folder and included in runtests.jl
| re = lnn.re | ||
| hess = x -> Zygote.hessian_reverse(x->sum(re(p)(x)), x) # we have to compute the whole hessian | ||
| hess = hess(x)[M+1:end, M+1:end] # takes only velocities | ||
| inv_hess = GenericLinearAlgebra.pinv(hess) |
manyfeatures
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Related to JuliaDiff/FiniteDiff.jl#147 |
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PR adds Lagrangian NN implementation (#352)
Evident drawbacks:
One sample training loss function:
More meaningful example is coming