Ghent University Academic Bibliography

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Assessing high-order effects in feature importance via predictability decomposition

Marlis Ontivero Ortega, Luca Faes, Jesus M. Cortes, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2025) PHYSICAL REVIEW E. 111(3).
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- Journal Article
- A1
- open access
Network representation of higher-order interactions based on information dynamics

Gorana Mijatovic, Yuri Antonacci, Michal Javorka, Daniele Marinazzo (UGent) , Sebastiano Stramaglia and Luca Faes

(2025) IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING. 12(3). p.1872-1884
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- A2
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Disentangling high-order effects in the transfer entropy

Sebastiano Stramaglia, Luca Faes, Jesus M. Cortes and Daniele Marinazzo (UGent)

(2024) PHYSICAL REVIEW RESEARCH. 6(3).
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Gradients of O-information highlight synergy and redundancy in physiological applications

Tomas Scagliarini, Laura Sparacino, Luca Faes, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2024) FRONTIERS IN NETWORK PHYSIOLOGY. 3.
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Assessing high-order links in cardiovascular and respiratory networks via static and dynamic information measures

Gorana Mijatovic, Laura Sparacino, Yuri Antonacci, Michal Javorka, Daniele Marinazzo (UGent) , Sebastiano Stramaglia and Luca Faes

(2024) IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY. 5. p.846-858
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- A2
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Gradients of O-information : low-order descriptors of high-order dependencies

Tomas Scagliarini, Davide Nuzzi, Yuri Antonacci, Luca Faes, Fernando E. Rosas, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2023) PHYSICAL REVIEW RESEARCH. 5(1).
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A new framework for the time- and frequency-domain assessment of high-order interactions in networks of random processes

Luca Faes, Gorana Mijatovic, Yuri Antonacci, Riccardo Pernice, Chiara Bara, Laura Sparacino, Marco Sammartino, Alberto Porta, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2022) IEEE TRANSACTIONS ON SIGNAL PROCESSING. 70. p.5766-5777
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- Conference Paper
Inclusion of Instantaneous Influences in the Spectral Decomposition of Causality: Application to the Control Mechanisms of Heart Rate Variability

Davide Nuzzi, Luca Faes, Michal Javorka, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2021) 28TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2020). In European Signal Processing Conference p.930-934
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Extending the spectral decomposition of Granger causality to include instantaneous influences : application to the control mechanisms of heart rate variability

D. Nuzzi, S. Stramaglia, M. Javorka, Daniele Marinazzo (UGent) , A. Porta and Luca Faes

(2021) PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES. 379(2212).
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Multivariate correlation measures reveal structure and strength of brain–body physiological networks at rest and during mental stress

Riccardo Pernice, Yuri Antonacci, Matteo Zanetti, Alessandro Busacca, Daniele Marinazzo (UGent) , Luca Faes and Giandomenico Nollo

(2021) FRONTIERS IN NEUROSCIENCE. 14.

Academic Bibliography

Assessing high-order effects in feature importance via predictability decomposition

Network representation of higher-order interactions based on information dynamics

Disentangling high-order effects in the transfer entropy

Gradients of O-information highlight synergy and redundancy in physiological applications

Assessing high-order links in cardiovascular and respiratory networks via static and dynamic information measures

Gradients of O-information : low-order descriptors of high-order dependencies

A new framework for the time- and frequency-domain assessment of high-order interactions in networks of random processes

Inclusion of Instantaneous Influences in the Spectral Decomposition of Causality: Application to the Control Mechanisms of Heart Rate Variability

Extending the spectral decomposition of Granger causality to include instantaneous influences : application to the control mechanisms of heart rate variability

Multivariate correlation measures reveal structure and strength of brain–body physiological networks at rest and during mental stress

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