3 papers
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…
cs.LG2026
Temporal-Conditioned Normalizing Flows for Multivariate Time Series Anomaly Detection
David Baumgartner, Helge Langseth, Kenth Engø-Monsen +1
This paper introduces temporal-conditioned normalizing flows (tcNF), a novel framework that addresses anomaly detection in time series data with accurate modeling of temporal depen…
cs.AI2025
Causal computations in Semi Markovian Structural Causal Models using divide and conquer
Anna Rodum Bjøru, Rafael Cabañas, Helge Langseth +1
Recently, Bjøru et al. proposed a novel divide-and-conquer algorithm for bounding counterfactual probabilities in structural causal models (SCMs). They assumed that the SCMs were…