3 citations · 5 across the 4 of their papers we have counts for
4 papers
Measuring hierarchically-organized interactions in dynamic networks through spectral entropy rates: theory, estimation, and illustrative application to physiological networks
Laura Sparacino, Yuri Antonacci, Gorana Mijatovic +1
Recent advances in signal processing and information theory are boosting the development of new approaches for the data-driven modelling of complex network systems. In the fields o…
Assessing High-Order Links in Cardiovascular and Respiratory Networks via Static and Dynamic Information Measures
Gorana Mijatovic, Laura Sparacino, Yuri Antonacci +4
The network representation is becoming increasingly popular for the description of cardiovascular interactions based on the analysis of multiple simultaneously collected variables.…
A method to assess Granger causality, isolation and autonomy in the time and frequency domains: theory and application to cerebrovascular variability
Laura Sparacino, Yuri Antonacci, Chiara Barà +3
Concepts of Granger causality (GC) and Granger autonomy (GA) are central to assess the dynamics of coupled physiologic processes. While causality measures have been already propose…
Gradients of O-information: low-order descriptors of high-order dependencies
Tomas Scagliarini, Davide Nuzzi, Yuri Antonacci +4
O-information is an information-theoretic metric that captures the overall balance between redundant and synergistic information shared by groups of three or more variables. To com…