390 citations · 3.5k across the 79 of their papers we have counts for
7 papers · 1 filter
Pattern detection in bipartite networks: a review of terminology, applications and methods
Zachary Neal, Annabel Cadieux, Diego Garlaschelli +7
Two dimensional matrices with binary (0/1) entries are a common data structure in many research fields. Examples include ecology, economics, mathematics, physics, psychometrics and…
Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints
Nicolò Vallarano, Matteo Bruno, Emiliano Marchese +5
Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. Rooted into statistical physics, the ERGMs framework has been successfully employed for re…
Enhanced reconstruction of weighted networks from strengths and degrees
Rossana Mastrandrea, Tiziano Squartini, Giorgio Fagiolo +1
Network topology plays a key role in many phenomena, from the spreading of diseases to that of financial crises. Whenever the whole structure of a network is unknown, one must reso…
Algebraic characterization of binary graphs
Tiziano Squartini
One of the fundamental concepts in the statistical mechanics field is that of ensemble. Ensembles of graphs are collections of graphs, defined according to certain rules. The two m…
Reciprocity of weighted networks
Tiziano Squartini, Francesco Picciolo, Franco Ruzzenenti +1
All types of networks arise as intricate combinations of dyadic building blocks formed by pairs of vertices. In directed networks, the dyadic patterns are entirely determined by re…
Null Models of Economic Networks: The Case of the World Trade Web
Giorgio Fagiolo, Tiziano Squartini, Diego Garlaschelli
In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the b…
Analytical maximum-likelihood method to detect patterns in real networks
Tiziano Squartini, Diego Garlaschelli
In order to detect patterns in real networks, randomized graph ensembles that preserve only part of the topology of an observed network are systematically used as fundamental null…