Normal or not? How to detect anomalies in networks

Project specs




Gesine Reinert



Funding agency





Complex interactions such as financial transactions or links between computers can often be visualised as networks. Anomalies in such networks may indicate deviant behaviour. How can we detect such anomalies?

In this video we shall encounter a statistical test called Monte Carlo test to address this issue. The Monte Carlo test can also be applied in many other scenarios.

The scientific lead for this video was Prof Gesine Reinert, University of Oxford, Department of Statistics

Researcher Profile

COSTNET is a European COST collaboration of more than 500 statisticians and other quantitative scientists from 34 countries on the development of novel inference methods for network data science. It is lead by Prof. Ernst Wit (USI/RuG) and the core management team involving Gesine Reinert (Oxford), Goeran Kauermann (LMU, Munich), Veronica Vinciotti (Trento), Claire Gormley (UCD, Dublin), Clelia di Serio (UniSR, Milano), Steffen Lauritzen (Copenhagen), Anuska Ferligoj and Vladimir Batagelj (Ljubljana), Arnoldo Frigessi (Oslo).

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