PROGRAM

LCN2 seminar - Assag Almog (LION): 'From the brain to the economy: finding communities in networks and correlation matrices'

Date:

Time:

16:00 hrs

Location:

HL106, Niels Bohrweg, Leiden

 

LCN2 Seminar Assaf Almog

Assaf Almog from the Leiden Institute of Physics will give an LCN2 seminar on February 26th at 16:00 in room HL106, titled 'From the brain to the economy: finding communities in networks and correlation matrices'.


Abstract

The mesoscopic organization of complex systems, from financial markets to the brain, is an intermediate between the microscopic dynamics of individual units (stocks or neurons, in the mentioned cases), and the macroscopic dynamics of the system as a whole. Indeed, many systems tend to organized in a modular way, with functionally related units being correlated with each other, while at the same time being relatively less (or even negatively) correlated with functionally dissimilar ones. The empirical identification of such emergent organization is challenging due to unavoidable information loss, when inferring the structure from the original time series activity data.


In this talk, I will present a modularity based community detection approach for correlation matrices. The method uses maximum-entropy null model designed specifically for correlation matrices (and not networks) that is able to filter out both unit-specific noise and system-wide dependencies. This results in identification of meso-scale functional modules that are internally correlated and mutually anti-correlated. I will present applications to brain networks, financial markets, and international trade.


Lastly, using the maximum-entropy framework, I will discuss a new null model for community detection. This "enhanced" null model is able provide link expectations based on both the strengths and the topology of the network. The application of this model to the International Trade Network reveals differences with respect to the standard approach.

Events

6 - 7 June 2019

Casimir Open Days 2019link

24 - 28 June 2019

BioBusiness Summer Schoollink