Your link autograd.jl seems dead ?
Le vendredi 26 août 2016 08:51:30 UTC+2, Deniz Yuret a écrit : > > Announcing AutoGrad.jl <https://github.com/denizyuret/AutoGrad.jl>: an > automatic differentiation package for Julia. It is a Julia port of the > popular Python autograd <https://github.com/HIPS/autograd> package. It > can differentiate regular Julia code that includes loops, conditionals, > helper functions, closures etc. by keeping track of the primitive > operations and using this execution trace to compute gradients. It uses > reverse mode differentiation (a.k.a. backpropagation) so it can efficiently > handle functions with array inputs and scalar outputs. It can compute > gradients of gradients to handle higher order derivatives. > > Large parts of the code are directly ported from the Python autograd > <https://github.com/HIPS/autograd> package. I'd like to thank autograd > author Dougal Maclaurin for his support. See (Baydin et al. 2015) > <https://arxiv.org/abs/1502.05767> for a general review of automatic > differentiation, autograd tutorial > <https://github.com/HIPS/autograd/blob/master/docs/tutorial.md> for some > Python examples, and Dougal's PhD thesis for design principles. JuliaDiff > <http://www.juliadiff.org/> has alternative differentiation tools for > Julia. > > best, > deniz > >
