81 citations · 273 across the 10 of their papers we have counts for
10 papers
Causal learning with sufficient statistics: an information bottleneck approach
Daniel Chicharro, Michel Besserve, Stefano Panzeri
The inference of causal relationships using observational data from partially observed multivariate systems with hidden variables is a fundamental question in many scientific domai…
Conditionally-additive-noise Models for Structure Learning
Daniel Chicharro, Stefano Panzeri, Ilya Shpitser
Constraint-based structure learning algorithms infer the causal structure of multivariate systems from observational data by determining an equivalent class of causal structures co…
MAXENT3D_PID: An Estimator for the Maximum-entropy Trivariate Partial Information Decomposition
Abdullah Makkeh, Daniel Chicharro, Dirk Oliver Theis +1
Chicharro (2017) introduced a procedure to determine multivariate partial information measures within the maximum entropy framework, separating unique, redundant, and synergistic c…
The identity of information: how deterministic dependencies constrain information synergy and redundancy
Daniel Chicharro, Giuseppe Pica, Stefano Panzeri
Understanding how different information sources together transmit information is crucial in many domains. For example, understanding the neural code requires characterizing how dif…
Quantifying multivariate redundancy with maximum entropy decompositions of mutual information
Daniel Chicharro
Williams and Beer (2010) proposed a nonnegative mutual information decomposition, based on the construction of redundancy lattices, which allows separating the information that a s…
Invariant components of synergy, redundancy, and unique information among three variables
Giuseppe Pica, Eugenio Piasini, Daniel Chicharro +1
In a system of three stochastic variables, the Partial Information Decomposition (PID) of Williams and Beer dissects the information that two variables (sources) carry about a thir…