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.CL2024
PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models
Lemei Zhang, Peng Liu, Marcus Tiedemann Oekland Henriksboe +3
With the rapid advancement of Natural Language Processing in recent years, numerous studies have shown that generic summaries generated by Large Language Models (LLMs) can sometime…