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RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [80, 3, 1, 1]] is at version 2; expected version 1 instead. Hint: …
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### Description
The NSL-KDD dataset, provided by the University of New Brunswick's Canadian Institute for Cybersecurity, serves as a revised version of the original KDD Cup 1999 dataset. It is exte…
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Hi,
I believe your implementation of the AUPRO score is missing an important part (or at least i couldnt find it).
https://github.com/gasharper/PyramidFlow/blob/6977d5a8294276bf7a9952477235f219…
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Couple of stuff to look at:
- [x] `07.Unsupervised_Learning-Transformations_and_Dimensionality_Reduction` fix `digits_plot` no output in jupyter-lab
- [x] `14.Model_Complexity_and_GridSearchCV` Av…
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https://github.com/DASE4/ComGA/blob/7006f0d0563f8bba10c7636e126539190538dd7f/anomaly_detection.py#L51,Why is the m here the number of edges of the original graph?
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My re-implemented results in unsupervised anomaly detection (1000 epochs for all the three datasets):
**Ped2: 95.0%
Avenue: 82.2%
ShanghaiTech: 72.9%**
The result on Avenue is much lower than tha…
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Hello,
I tried to use the AutoEncoder for unsupervised anomaly detection but I get the error as in the title. I am not sure what I did wrong, when I tried the AutoEncoder with synthetic generated d…
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A single patient commonly undergoes several MRI sessions across time (i.e., first session at month 0, second session at month X, third session at month Y, etc.). Images are then analyzed to explore lo…
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Can I understand the settings in the training downstream segmentation network by this way ?
1. There are only 500 images per anomlay class for training. But in the paper, per anomaly class has 1000 i…
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**Is your feature request related to a problem? Please describe.**
The current evaluation metrics in `evaluate/anomaly.py` assume that a ground truth available. However, in many time series anomaly d…