You could do the L2 norm using the regular convolution by using the identity ||w-x||^2 = ||w||^2-2||w dot x||+||x||^2
and using http://deeplearning.net/software/theano/library/tensor/nnet/neighbours.html#theano.tensor.nnet.neighbours.images2neibs to help with the ||x||^2 and regular convolution to compute the ||w dot x|| term. Other nonlinearities might be more tricky. On Monday, July 25, 2016 at 12:08:56 PM UTC-7, Geppetto Null wrote: > > Hi everyone, > > I would like to modify the 2D convolution in order to introduce some > non-linear operation. For instance, instead of performing w^Tx+b = > dot(w,x)+b in each receptive field (i.e., patch of the input --as is by > default), I would like to perform the operation ||w-x||^2+b to each > receptive field, or some other non-linear operation (some other norm, for > example L-1). Is this doable in Theano/Lasagne? > > Thank you very much in advance. > Best, > Christos > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
