| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | ✓ Link | 0.470 | | Auto-Encoder with Regression (AER) | 2022-12-27 |
| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | ✓ Link | 0.391 | | LSTM-DT | 2022-12-27 |
| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | ✓ Link | 0.317 | | LSTM-VAE | 2022-12-27 |
| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | ✓ Link | 0.314 | | LSTM-AE | 2022-12-27 |
| Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series | ✓ Link | 0.27 ±0.0 | 0.51 ± 0.0 | MERLIN | 2022-12-21 |
| Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series | ✓ Link | 0.25 ±0.0 | 0.66 ± 0.0 | Maximally Divergent Intervals (MDI) | 2022-12-21 |
| Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series | ✓ Link | 0.23 ±0.021 | 0.63 ±0.009 | Graph Augmented Normalizing Flows (GANF) | 2022-12-21 |
| Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series | ✓ Link | 0.18 ±0.003 | 0.56 ±0.003 | Transformer Network for Anomaly Detection (TranAD) | 2022-12-21 |
| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | ✓ Link | 0.162 | | TadGAN | 2022-12-27 |
| Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series | ✓ Link | 0.16 ± 0.013 | 0.58 ±0.01 | Autoencoder (AE) | 2022-12-21 |
| AER: Auto-Encoder with Regression for Time Series Anomaly Detection | ✓ Link | 0.124 | | ARIMA | 2022-12-27 |
| Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series | ✓ Link | 0.07 ±0.011 | 0.56 ± 0.0019 | Robust Random Cut Forest (RRCF) | 2022-12-21 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.8188 ±0.0041 | KAN-AD | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.8001 | SubLOF | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.7489 | KAN | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.7145 | FCVAE | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.6550 | SAND | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.6432 | LSTMAD | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.5969 | FITS | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.5699 | OFA | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.5458 | AT | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.5109 | SRCNN | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.4599 | TranAD | 2024-11-01 |
| KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks | ✓ Link | | 0.4536 | TimesNet | 2024-11-01 |