1.6k citations · 4.2k across the 72 of their papers we have counts for
6 papers · 1 filter
Interest communities and flow roles in directed networks: the Twitter network of the UK riots
Mariano Beguerisse-Díaz, Guillermo Garduño-Hernández, Borislav Vangelov +2
Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only…
Finding role communities in directed networks using Role-Based Similarity, Markov Stability and the Relaxed Minimum Spanning Tree
Mariano Beguerisse-Díaz, Borislav Vangelov, Mauricio Barahona
We present a framework to cluster nodes in directed networks according to their roles by combining Role-Based Similarity (RBS) and Markov Stability, two techniques based on flows.…
The stability of a graph partition: A dynamics-based framework for community detection
Jean-Charles Delvenne, Michael T. Schaub, Sophia N. Yaliraki +1
Recent years have seen a surge of interest in the analysis of complex networks, facilitated by the availability of relational data and the increasingly powerful computational resou…
On Periodic Reference Tracking Using Batch-Mode Reinforcement Learning with Application to Gene Regulatory Network Control
Aivar Sootla, Natalja Strelkowa, Damien Ernst +2
In this paper, we consider the periodic reference tracking problem in the framework of batch-mode reinforcement learning, which studies methods for solving optimal control problems…
Structure of complex networks: Quantifying edge-to-edge relations by failure-induced flow redistribution
Michael T. Schaub, Jörg Lehmann, Sophia N. Yaliraki +1
The analysis of complex networks has so far revolved mainly around the role of nodes and communities of nodes. However, the dynamics of interconnected systems is commonly focalised…
Toggling a Genetic Switch Using Reinforcement Learning
Aivar Sootla, Natalja Strelkowa, Damien Ernst +2
In this paper, we consider the problem of optimal exogenous control of gene regulatory networks. Our approach consists in adapting an established reinforcement learning algorithm c…