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SOTA
Anomaly Detection
Anomaly Detection On Ucr Anomaly Archive
Anomaly Detection On Ucr Anomaly Archive
Metrics
AUC ROC
Results
Performance results of various models on this benchmark
Columns
Model Name
AUC ROC
Paper Title
Repository
LSTMAD
0.6432
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
LSTM-AE
-
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
-
Autoencoder (AE)
0.58 ±0.01
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series
-
TranAD
0.4599
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
ARIMA
-
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
-
OFA
0.5699
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
Robust Random Cut Forest (RRCF)
0.56 ± 0.0019
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series
-
TadGAN
-
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
-
FCVAE
0.7145
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
SRCNN
0.5109
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
LSTM-VAE
-
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
-
KAN-AD
0.8188 ±0.0041
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
Auto-Encoder with Regression (AER)
-
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
-
Graph Augmented Normalizing Flows (GANF)
0.63 ±0.009
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series
-
SAND
0.6550
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
LSTM-DT
-
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
-
KAN
0.7489
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
SubLOF
0.8001
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
TimesNet
0.4536
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
-
MERLIN
0.51 ± 0.0
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series
-
0 of 24 row(s) selected.
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