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20042023
most citedKernel method for nonlinear Granger causality

413 citations · 1.7k across the 44 of their papers we have counts for

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physics.data-an2021★ 26 cited

Quantifying high-order interdependencies on individual patterns via the local O-information: theory and applications to music analysis

Tomas Scagliarini, Daniele Marinazzo, Yike Guo +2

High-order, beyond-pairwise interdependencies are at the core of biological, economic, and social complex systems, and their adequate analysis is paramount to understand, engineer,…

physics.data-an2015

Neural Networks with Non-Uniform Embedding and Explicit Validation Phase to Assess Granger Causality

Alessandro Montalto, Sebastiano Stramaglia, Luca Faes +3

A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dy…

physics.data-an2012

Information flow in a network model and the law of diminishing marginal returns

Daniele Marinazzo, Mario Pellicoro, Guorong Wu +2

We analyze a simple dynamical network model which describes the limited capacity of nodes to process the input information. For a suitable choice of the parameters, the information…

physics.data-an2011

Causal information approach to partial conditioning in multivariate data sets

Daniele Marinazzo, Mario Pellicoro, Sebastiano Stramaglia

When evaluating causal influence from one time series to another in a multivariate dataset it is necessary to take into account the conditioning effect of the other variables. In t…

physics.data-an2004

Extending Granger causality to nonlinear systems

Nicola Ancona, Daniele Marinazzo, Sebastiano Stramaglia

We consider extension of Granger causality to nonlinear bivariate time series. In this frame, if the prediction error of the first time series is reduced by including measurements…