3 papers
stat.ML2026
Revisiting OmniAnomaly for Anomaly Detection: performance metrics and comparison with PCA-based models
Bruna Alves, Ana Martins, Armando J. Pinho +1
Deep learning models have become the dominant approach for multivariate time series anomaly detection (MTSAD), often reporting substantial performance improvements over classical s…
stat.ML2026
Unified Taxonomy for Multivariate Time Series Anomaly Detection using Deep Learning
Bruna Alves, Armando J. Pinho, Sónia Gouveia
The topic of Multivariate Time Series Anomaly Detection (MTSAD) has grown rapidly over the past years, with a steady rise in publications and Deep Learning (DL) models becoming the…
stat.ML2026
Fast and Interpretable Autoregressive Estimation with Neural Network Backpropagation
AnaÃsa Lucena, Ana Martins, Armando J. Pinho +1
Autoregressive (AR) models remain widely used in time series analysis due to their interpretability, but convencional parameter estimation methods can be computationally expensive…