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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
A two-step sequential approach for hyperparameter selection in finite context models
José Contente, Ana Martins, Armando J. Pinho +1
Finite-context models (FCMs) are widely used for compressing symbolic sequences such as DNA, where predictive performance depends critically on the context length k and smoothing p…
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…