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Showing content from https://github.com/ForestsKing/D3R below:

ForestsKing/D3R: PyTorch implementation of "Drift doesn't Matter: Dynamic Decomposition with Dffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection" (NeurIPS 2023)

Download data. You can obtain two benchmarks from Google Cloud. The datasets are well pre-processed. For the SWaT dataset, you can apply for it by following its official tutorial. We unify the SWaT dataset to minute granularity and retain only continuous metrics:

'AIT201', 'AIT202', 'AIT203', 'AIT401', 'AIT402', 'AIT501',
'AIT502', 'AIT503', 'AIT504', 'DPIT301', 'FIT101', 'FIT201',
'FIT301', 'FIT401', 'FIT501', 'FIT502', 'FIT503', 'FIT504',
'FIT601', 'LIT101', 'LIT301', 'LIT401', 'PIT501', 'PIT502',
'PIT503'

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