Comments (2)
i is sample index and j is dimension index. so i for N, and j for d. std(z) is w.r.t. the whole vector, not values. hope it is clear?
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Thanks for your answer!
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Related Issues (20)
- loss question HOT 4
- Single GPU Training HOT 3
- Loss descent slowly HOT 1
- Checkpoints with 50 epochs HOT 1
- [Problem] problem occured when trained on custom dataset HOT 4
- difference between byol in table19 and simsiam? HOT 1
- larger batch size with linear scale does not work
- checkpoint for epoch 800
- Slow convergence with SGD linear evaluation HOT 1
- SyncBatchnorm usage in main_lincls.py HOT 2
- About the projection and prediction head dimension configs
- Loss collapse during training HOT 1
- About the shape of image[0] and image[1] HOT 1
- Pre-trained weights for SimCLR, MoCov2, BYOL, SwaV HOT 1
- The value of loss function nn.CosineSimilarity is negative HOT 1
- self.encoder.fc in builder.py
- which vector is used in experiment (the vector atfer predictor or after projection)?
- Why are training and testing so slow HOT 2
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