13 citations · 21 across the 10 of their papers we have counts for
10 papers
Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling
Jin Li, Kleanthis Malialis, Christos G. Panayiotou +1
In today's digital world, the generation of vast amounts of streaming data in various domains has become ubiquitous. However, many of these data are unlabeled, making it challengin…
Resilient Class-Incremental Learning: on the Interplay of Drifting, Unlabelled and Imbalanced Data Streams
Jin Li, Kleanthis Malialis, Marios Polycarpou
In today's connected world, the generation of massive streaming data across diverse domains has become commonplace. In the presence of concept drift, class imbalance, label scarcit…
Low Rank Transformer for Multivariate Time Series Anomaly Detection and Localization
Charalampos Shimillas, Kleanthis Malialis, Konstantinos Fokianos +1
Multivariate time series (MTS) anomaly diagnosis, which encompasses both anomaly detection and localization, is critical for the safety and reliability of complex, large-scale real…
The Battle of the Water Futures
Dennis Zanutto, Christos Michalopoulos, Lydia Tsiami +12
The highly anticipated 'Battle of the Water Networks' is back with a new challenge for the water community. This competition will be hosted at the 4th International Joint Conferenc…
Unsupervised Online Detection of Pipe Blockages and Leakages in Water Distribution Networks
Jin Li, Kleanthis Malialis, Stelios G. Vrachimis +1
Water Distribution Networks (WDNs), critical to public well-being and economic stability, face challenges such as pipe blockages and background leakages, exacerbated by operational…
Interpretable Event Diagnosis in Water Distribution Networks
André Artelt, Stelios G. Vrachimis, Demetrios G. Eliades +3
The increasing penetration of information and communication technologies in the design, monitoring, and control of water systems enables the use of algorithms for detecting and ide…
SiameseDuo++: Active Learning from Data Streams with Dual Augmented Siamese Networks
Kleanthis Malialis, Stylianos Filippou, Christos G. Panayiotou +1
Data stream mining, also known as stream learning, is a growing area which deals with learning from high-speed arriving data. Its relevance has surged recently due to its wide rang…
Online Detection of Water Contamination Under Concept Drift
Jin Li, Kleanthis Malialis, Stelios G. Vrachimis +1
Water Distribution Networks (WDNs) are vital infrastructures, and contamination poses serious public health risks. Harmful substances can interact with disinfectants like chlorine,…
Transformer-based Multivariate Time Series Anomaly Localization
Charalampos Shimillas, Kleanthis Malialis, Konstantinos Fokianos +1
With the growing complexity of Cyber-Physical Systems (CPS) and the integration of Internet of Things (IoT), the use of sensors for online monitoring generates large volume of mult…
Urban Water Consumption Forecasting Using Deep Learning and Correlated District Metered Areas
Kleanthis Malialis, Nefeli Mavri, Stelios G. Vrachimis +3
Accurate water consumption forecasting is a crucial tool for water utilities and policymakers, as it helps ensure a reliable supply, optimize operations, and support infrastructure…