This should be as simple as creating just one shared variable to train and then using it in different places in the network.
On Tuesday, July 12, 2016 at 9:48:28 AM UTC-7, André Ribeiro wrote: > > Hi, > > I am trying to create a CNN that share weights between 2 consecutive > layers. This is particularly interesting if we are looking into separable > filters. > For example: > If we want to approximate a 2d gaussian filter using a CNN, we could > potentially just have to learn a 1 layer 1d convolutional network (with k > elements) and apply it first in the x direction and then in the y > direction, instead of a 1 layer 2d convolutional network (with k^2 > elements). > > Any help here? > -- --- 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 [email protected]. For more options, visit https://groups.google.com/d/optout.
