CRAFTIIF uses 500 random analytic wavelet features across four families and five structured isolation forests to target four anomaly types, achieving first place on mTSBench VUS-PR at 0.463.
Extended isolation forest,
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cs.LG 2years
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PaAno+ extends the original PaAno with multiscale feature extraction, cross-variable fusion attention, and a temporal patch sorting pretext task to report state-of-the-art results on the TSB-AD benchmark for univariate and multivariate anomaly detection.
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CRAFTIIF: Cross-Resolution Analytic Four-Type Interpretable Isolation Forest for Multivariate Time Series Anomaly Detection
CRAFTIIF uses 500 random analytic wavelet features across four families and five structured isolation forests to target four anomaly types, achieving first place on mTSBench VUS-PR at 0.463.
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PaAno+: Multiscale Encoding and Cross-Variable Attention for Time Series Anomaly Detection
PaAno+ extends the original PaAno with multiscale feature extraction, cross-variable fusion attention, and a temporal patch sorting pretext task to report state-of-the-art results on the TSB-AD benchmark for univariate and multivariate anomaly detection.