time series

Change point detection (CPD) identifies abrupt and significant changes in sequential data, with applications in human activity …

Continuous physiological monitoring is central to emergency care, yet deploying trustworthy AI is challenging. While LLMs can translate …

Identifying the drivers of change in time-sensitive domains like healthcare is critical for reliable decision-making, yet explanations …

BACKGROUND Accurate and continuous monitoring of physiological stress is crucial, especially for patients with neurodegenerative …

Financial markets are complex systems characterized by high statistical noise, nonlinearity, volatility, and constant evolution. Thus, …

Online learning environments (OLEs) have seen a continuous increase over the past decade and a sudden surge in the last year, due to …

In this paper we present CoRoNNa a deep sequential framework for epidemic prediction that leverages a flexible combination of …

CoRoNNa is a deep framework for epidemic prediction that integrates mobility data and demographic information to analyze the impact of containment policies on COVID-19 spread.

We propose CoRoNNa, a deep framework for epidemic prediction to analyse the spread of COVID-19 and, potentially, of other unknown …

In this tutorial, we explored challenges in retention, and presented machine learning solutions to the difficulties in predicting student dropout rates from online courses.