You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
However, since the standard deviation of the normalized target signal is 1, lines 190 (output_freq = output_freq / torch.std(target_freq)) and 191 (target_freq = target_freq / torch.std(target_freq)) are redundant and do not have any function. These two lines have been removed.
I also realized that in the simulated data, this line generates 19 identical signals for the 19 input/output channels. Was this on purpose or is it a mistake?
I also noticed using all the loss components: trainValidateSegmentation(args=model_train_parameter([1, 1, 1, 1], './' + name + '_Simulate_5', "./" + name + "_simulate_data/"))
that loss1, loss2, loss3 lie within [0, 1] while loss4 is in the scale of hundreds.
Therefore I'm wondering if you used different data to generate the ensemble loss of figure 4?
Hello,
thanks a lot for open sourcing your code for this interesting work!
I think there is a bug in this line: shouldn't it be
output_freq = output_freq / torch.std(output_freq)
?Thanks in advance,
Christina
The text was updated successfully, but these errors were encountered: