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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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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Localizing synergies of hidden factors in complex systems : resting brain networks and hela geneexpression profile as case studies

Marlis Ontivero-Ortega, Gorana Mijatovic, Luca Faes, Fernando E. Rosas, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2025) ENTROPY. 27(8).
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Decomposing multivariate information rates in networks of random processes

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

(2025) PHYSICAL REVIEW E. 112(4).
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Partial information rate decomposition

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

(2025) PHYSICAL REVIEW LETTERS. 135(18).
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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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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

Academic Bibliography

Assessing high-order effects in feature importance via predictability decomposition

Network representation of higher-order interactions based on information dynamics

Localizing synergies of hidden factors in complex systems : resting brain networks and hela geneexpression profile as case studies

Decomposing multivariate information rates in networks of random processes

Partial information rate decomposition

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

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