7 papers
Fuzzy network jump models for soft dynamic clustering of graph-structured data
Federico P. Cortese
We introduce a fuzzy network jump model for clustering time-varying observations indexed by the nodes of a weighted graph. The framework allows flexible graph representations with…
Infinite hidden Markov models for cylindrical data
Federico P. Cortese, Luca Rossini
We propose an infinite hidden Markov model for cylindrical time series with von Mises-Gamma emissions. Posterior inference is performed using a beam sampler combining conjugate upd…
A comparison between initialization strategies for the infinite hidden Markov model
Federico P. Cortese, Luca Rossini
Infinite hidden Markov models provide a flexible framework for modeling time-series with structural changes and complex dynamics, without requiring the number of latent states to b…
Robust State-Conditional Feature-Weighted Jump Models for Temporal Clustering
Federico P. Cortese, Alessio Farcomeni
We propose a robust feature-weighted jump model for time-dependent clustering. A penalty is used to encourage smoothness of transitions over time, while robustness is achieved thro…
Fuzzy Jump Models for Soft and Hard Clustering of Multivariate Time Series Data
Federico P. Cortese, Antonio Pievatolo, Elisa Maria Alessi
Statistical jump models have been recently introduced to detect persistent regimes by clustering temporal features and discouraging frequent regime changes. However, they are limit…
Spatio-Temporal Jump Model for Urban Thermal Comfort Monitoring
Federico P. Cortese, Antonio Pievatolo
Thermal comfort is essential for well-being in urban spaces, especially as cities face increasing heat from urbanization and climate change. Existing thermal comfort models usually…