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ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids., , , , and . IEEE Access, (2020)Towards efficient deep autoencoders for multivariate time series anomaly detection., , , and . CoRR, (2024)CPDGA: Change point driven growing auto-encoder for lifelong anomaly detection., , and . Knowl. Based Syst., (2022)Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification., , , and . IJCNN, page 1-7. IEEE, (2021)LIFEWATCH: Lifelong Wasserstein Change Point Detection., , , , and . IJCNN, page 1-8. IEEE, (2022)Distributed Continual Intrusion Detection: A Collaborative Replay Framework., , and . IEEE Big Data, page 3255-3263. IEEE, (2023)The class imbalance problem in deep learning., , , , , and . Mach. Learn., 113 (7): 4845-4901 (July 2024)Spatial autocorrelation and entropy for renewable energy forecasting, , , and . Data Mining and Knowledge Discovery, 33 (3): 698--729 (2019)Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification., , , , , and . Sensors, 20 (14): 3906 (2020)Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data., , , , and . DS, volume 12986 of Lecture Notes in Computer Science, page 461-471. Springer, (2021)