An Exposed Closed-Loop Model for Customer-Driven Service Assurance Automation. - Min Xie 006; Foivos Michelinakis; Thomas Dreibholz; Joan S. Pujol Roig; Sara Malacarne; Sayantini Majumdar; Wint Yi Poe; Ahmed Elmokashfi (EuCNC/6G Summit, 2021)

Vector Quantized Time Series Generation with a Bidirectional Prior Model. - Daesoo Lee; Sara Malacarne; Erlend Aune (AISTATS, 2023)

Circle Attention: Forecasting Network Traffic by Learning Interpretable Spatial Relationships from Intersecting Circles. - Espen Haugsdal; Sara Malacarne; Massimiliano Ruocco (ECML/PKDD (7), 2023)

Masked Generative Modeling with Enhanced Sampling Scheme. - Daesoo Lee; Erlend Aune; Sara Malacarne (CoRR, 2023)

Explainable Anomaly Detection using Masked Latent Generative Modeling. - Daesoo Lee; Sara Malacarne; Erlend Aune (CoRR, 2023)

AI Anomaly Detection for Cloudified Mobile Core Architectures. - Foivos Michelinakis; Joan S. Pujol Roig; Sara Malacarne; Min Xie 006; Thomas Dreibholz; Sayantini Majumdar; Wint Yi Poe; Georgios Patounas; Carmen Guerrero; Ahmed Elmokashfi; Vasileios Theodorou (IEEE Trans. Netw. Serv. Manag., 2023)

SiamTST: A Novel Representation Learning Framework for Enhanced Multivariate Time Series Forecasting applied to Telco Networks. - Simen Kristoffersen; Peter Skaar Nordby; Sara Malacarne; Massimiliano Ruocco; Pablo Ortiz (CoRR, 2024)

Explainable time series anomaly detection using masked latent generative modeling. - Daesoo Lee; Sara Malacarne; Erlend Aune (Pattern Recognit., 2024)

Closing the Gap Between Synthetic and Ground Truth Time Series Distributions via Neural Mapping. - Daesoo Lee; Sara Malacarne; Erlend Aune (CoRR, 2025)