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?

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