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cs.AI2026
Anomaly detection in time-series via inductive biases in the latent space of conditional normalizing flows
David Baumgartner, Eliezer de Souza da Silva, Iñigo Urteaga
Deep generative models for anomaly detection in multivariate time-series are typically trained by maximizing observed data likelihood. However, likelihood in observation space meas…
cs.AI2026
CINDI: Conditional Imputation and Noisy Data Integrity with Flows in Power Grid Data
David Baumgartner, Helge Langseth, Heri Ramampiaro
Real-world multivariate time series, particularly in critical infrastructure such as electrical power grids, are often corrupted by noise and anomalies that degrade the performance…