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dongliangchang avatar dongliangchang commented on August 26, 2024 1

Yes. Please see Section III.A The Discriminality Component for details.

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dongliangchang avatar dongliangchang commented on August 26, 2024

dot([0,1,0].t(), [1,2,3].t()) = [0,2,0].t()
matrix(diag([0,1,0].t()), [1,2,3].t()) = [0,2,0].t()
So, the code and the paper is consistent.
CWA could be visualized as a random channel-dropping operation in each channel group.

from mutual-channel-loss.

dongliangchang avatar dongliangchang commented on August 26, 2024

535949063158081301

from mutual-channel-loss.

Hoodythree avatar Hoodythree commented on August 26, 2024

Got it.Thanks for the response.

from mutual-channel-loss.

AND2797 avatar AND2797 commented on August 26, 2024
foo = [1] * 2 + [0] *  1
bar = []
for i in range(200):
    random.shuffle(foo)
    bar += foo
bar = [bar for i in range(nb_batch)]

I had a small question about the code, here foo = [1] * 2 + [0] * 1 is only good for 3 channels correct? If we want to increase the number of channels (say 5), then foo = [1] * 3 + [0] * 2 is necessary, correct?

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