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View Code? Open in Web Editor NEWPyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
License: MIT License
PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
License: MIT License
Hi Author, could you please provide the environment file as you mentioned in the environment installation section? Thanks
An error occurred during Hydra's exception formatting:
AsswerionError()
It seems the method prior_association() can not back propagate gradient to train Ws, or maybe I misunderstood?
anomaly_transformer_pytorch/model.py
Lines 41 to 45 in 6d15200
according to paper, is this the right way?
gaussian = 1 / math.sqrt(2 * math.pi) / self.sigma * torch.exp(- 0.5 * (p / self.sigma).pow(2))
There is an issue with the loss:
anomaly_transformer_pytorch/train.py
Line 53 in 6d15200
How should I process my data?The function "get_data" has not been defined.
when I trian the model , I met the problem. Can you give me some suggestions?
Hi author, could you please provide the requirements.txt file?
Your research is very impressive and wonderful. However, I have one question while reading the paper.
in this paper, For the maximize phase, we optimize the series-association to enlarge the association discrepancy. This process forces the series-association to pay more attention to the non-adjacent horizon.
Maximize phases seem to focus more on series-association on adjacent horizon, but why is this non-adjacent horizon?
In my opinion, if the sigma of the prior association is much less than 1, the series association will only look at more adjacent areas.
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