The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and –more recently – correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. T...
Revealing the structural features of a complex system from the observed collective dynamics is a fun...
Networked structures arise in a wide array of different contexts such as technological and transport...
We review the main tools which allow for the statistical characterization of weighted networks. We t...
<div><p>The statistical mechanical approach to complex networks is the dominant paradigm in describi...
The statistical mechanical approach to complex networks is the dominant paradigm in describing natur...
Abstract. Topological landscape is introduced for networks with functions defined on the nodes. By e...
Networked structures arise in a wide array of different contexts such as technological and transport...
Networked structures arise in a wide array of different contexts such as technological and transport...
Persistent homology is an emerging tool to identify robust topological features underlying the stru...
In Network Science node neighbourhoods, also called ego-centered networks have attracted large atten...
Networks have become a general concept to model the structure of arbitrary relationships among entit...
Proceedings of the conference \"Complex networks: structure, function and processes\", Kolkata (Sate...
Proceedings of the conference \"Complex networks: structure, function and processes\", Kolkata (Sate...
One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons ...
A statistical physics perspective of complex networks: from the architecture of the Internet and the...
Revealing the structural features of a complex system from the observed collective dynamics is a fun...
Networked structures arise in a wide array of different contexts such as technological and transport...
We review the main tools which allow for the statistical characterization of weighted networks. We t...
<div><p>The statistical mechanical approach to complex networks is the dominant paradigm in describi...
The statistical mechanical approach to complex networks is the dominant paradigm in describing natur...
Abstract. Topological landscape is introduced for networks with functions defined on the nodes. By e...
Networked structures arise in a wide array of different contexts such as technological and transport...
Networked structures arise in a wide array of different contexts such as technological and transport...
Persistent homology is an emerging tool to identify robust topological features underlying the stru...
In Network Science node neighbourhoods, also called ego-centered networks have attracted large atten...
Networks have become a general concept to model the structure of arbitrary relationships among entit...
Proceedings of the conference \"Complex networks: structure, function and processes\", Kolkata (Sate...
Proceedings of the conference \"Complex networks: structure, function and processes\", Kolkata (Sate...
One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons ...
A statistical physics perspective of complex networks: from the architecture of the Internet and the...
Revealing the structural features of a complex system from the observed collective dynamics is a fun...
Networked structures arise in a wide array of different contexts such as technological and transport...
We review the main tools which allow for the statistical characterization of weighted networks. We t...