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Hi, thanks for sharing your work. I noticed that the outliers seem not to be used in the code (as shown below). However, according to the description in the paper, outliers should be assigned to the nearest pseudo category. I would like to know where this operation is carried out.
in em.py: nums.index_add_(0, labels[labels != -1], torch.ones(labels[labels != -1].shape[0], 1).float().cuda())
The text was updated successfully, but these errors were encountered:
Hi, thanks for sharing your work. I noticed that the outliers seem not to be used in the code (as shown below). However, according to the description in the paper, outliers should be assigned to the nearest pseudo category. I would like to know where this operation is carried out.
in em.py: nums.index_add_(0, labels[labels != -1], torch.ones(labels[labels != -1].shape[0], 1).float().cuda())
The text was updated successfully, but these errors were encountered: