1 code implementation • 16 Jan 2019 • Daniele Marinazzo, Leonardo Angelini, Mario Pellicoro, Sebastiano Stramaglia
We consider the formalism of information decomposition of target effects from multi-source interactions, i. e. the problem of defining unique, redundant (or shared), and synergistic (or complementary) components of the information that a set of source variables provides about a target, and apply it to the two-dimensional Ising model as a paradigm of a critically transitioning system.
Statistical Mechanics
1 code implementation • 20 Mar 2008 • Daniele Marinazzo, Mario Pellicoro, Sebastiano Stramaglia
We apply the proposed approach to a network of chaotic maps and to a simulated genetic regulatory network: it is shown that the underlying topology of the network can be reconstructed from time series of node's dynamics, provided that a sufficient number of samples is available.
Disordered Systems and Neural Networks Exactly Solvable and Integrable Systems Quantitative Methods
1 code implementation • 16 Nov 2007 • Daniele Marinazzo, Mario Pellicoro, Sebastiano Stramaglia
Important information on the structure of complex systems, consisting of more than one component, can be obtained by measuring to which extent the individual components exchange information among each other.
Disordered Systems and Neural Networks Exactly Solvable and Integrable Systems
