Bin Li, Carsten Jentsch and Emmanuel Müller. Prototypes as Explanation for Time SeriesAnomaly Detection. [pdf]

Hongjing Zhang, Fangzhou Cheng and Aparna Pandey. One-Class Predictive Autoencoder Towards Unsupervised Anomaly Detection on Industrial Time Series. [pdf]

Parastoo Kamranfar, David Lattanzi, Amarda Shehu and Daniel Barbara. Multiple Instance Learning for Detecting Anomalies over Sequential Real-World Datasets. [pdf]

Ruichuan Zhang, Fangzhou Cheng and Aparna Pandey. Representation Learning Using a Multi-Branch Transformer for Industrial Time Series Anomaly Detection. [pdf]

Taylor Dinkins, Sharmodeep Bhattacharyya, Shirshendu Chatterjee, Sabrina Reis and Weng-Keen Wong. Towards Explainable Precision Change point Detection through LinearDecomposition. [pdf]