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Biological Cybernetics|October 13, 2010
Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactionsLuca Faes, Giandomenico NolloBiological Cybernetics|January 30, 2013
Measuring frequency domain granger causality for multiple blocks of interacting time seriesLuca Faes, Giandomenico NolloMedical & Biological Engineering & Computing|August 29, 2006
Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variabilityLuca Faes, Giandomenico NolloNeuroscience and Biobehavioral Reviews|August 25, 2012
Social neuroscience and hyperscanning techniques: past, present and futureFabio Babiloni, Laura AstolfiScandinavian Journal of Psychology|July 22, 2024
Comparison of the symptom networks of long-COVID and chronic fatigue syndrome: From modularity to connectionismMichael E Hyland, Yuri Antonacci, Alison M BaconPlos One|October 15, 2014
MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropyAlessandro Montalto, Luca Faes, Daniele MarinazzoComputers in Biology and Medicine|March 23, 2011
Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability seriesLuca Faes, Giandomenico Nollo, Alberto PortaAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 16, 2007
Mutual nonlinear prediction of cardiovascular variability series: comparison between exogenous and autoregressive exogenous modelsLuca Faes, Alberto Porta, Giandomenico NolloBiomedizinische Technik. Biomedical Engineering|October 26, 2006
Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability seriesLuca Faes, Roberta Cucino, Giandomenico NolloPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|October 15, 2008
Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: comparison among different strategies based on k nearest neighborsLuca Faes, Alberto Porta, Giandomenico NolloPageof 32