Memristive networks: from graph theory to statistical physics

A simple solvable model of memristive networks suggests a correspondence between the asymptotic states of memristors and the Ising model.

EPL 125, 1 (2019)

A. Zegarac, F. Caravelli

LQ placeholderMemristive networks: from graph theory to statistical physics

We provide an introduction to a very specific toy model of memristive networks, for which an exact differential equation for the internal memory which contains the Kirchhoff laws is known. In particular, we highlight how the circuit topology enters the dynamics via an analysis of directed graph. We try to highlight in particular the connection between the asymptotic states of memristors and the Ising model, and the relation to the dynamics and statics of disordered systems.

LQ placeholderNetwork valuation in financial systems

Network valuation in financial systems

P. Barucca, M. Bardoscia, F. Caccioli, M. D’Errico, G. Visentin, G. Caldarelli, S. Battiston

Mathematical Finance

LQ placeholderThe space of functions computed by deep layered machines

The space of functions computed by deep layered machines

A. Mozeika, B. Li, D. Saad

Sub. to Physical Review Letters

LQ placeholderReplica analysis of overfitting in generalized linear models

Replica analysis of overfitting in generalized linear models

T. Coolen, M. Sheikh, A. Mozeika, F. Aguirre-Lopez, F. Antenucci

Sub. to Journal of Physics A

LQ placeholderTaming complexity

Taming complexity

M. Reeves, S. Levin, T. Fink, A. Levina

Harvard Business Review

LQ placeholderReplica analysis of Bayesian data clustering

Replica analysis of Bayesian data clustering

A. Mozeika, T. Coolen

Journal of Physics A

LQ placeholderDegree-correlations in a bursting dynamic network model

Degree-correlations in a bursting dynamic network model

F. Vanni, P. Barucca

Journal of Economic Interaction and Coordination

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