6 citations · 6 across the 7 of their papers we have counts for
8 papers
Likelihood-based anomaly detection in preferential attachment networks
Qiu Liang, Remco van der Hofstad, Nelly Litvak
Preferential attachment (PA) network is a widely used model for capturing the growth dynamics of real-world networks, in which newly arriving vertices are more likely to connect to…
Power-law hypothesis and (un)fairness of PageRank on undirected multi-type PAMs
Christian Borgs, Florian Henning, Remco van der Hofstad +1
The preferential attachment model (PAM) describes the sequential growth of a network based on the "rich-get-richer" principle. Several versions of it have become established for mo…
The stochastic block model has the overlap graph property for modularity
Shankar Bhamidi, David Gamarnik, Remco van der Hofstad +4
The overlap gap property (OGP) is a statement about the geometry of near-optimal solutions. Exhibiting OGP implies failure of a class of local algorithms; and has been observed to…
Degrees in Preferential Attachment Networks with an Anomaly
Qiu Liang, Remco van der Hofstad, Nelly Litvak
We consider a preferential attachment model that incorporates an anomaly. Our goal is to understand the evolution of the network before and after the occurrence of the anomaly by s…
Value of risk-contact data from digital contact monitoring apps in infectious disease modeling
Martijn H. H. Schoot Uiterkamp, Willian J. van Dijk, Hans Heesterbeek +3
In this paper, we present a simple method to integrate risk-contact data, obtained via digital contact monitoring (DCM) apps, in conventional compartmental transmission models. Dur…
Power-law hypothesis for PageRank on undirected graphs
Florian Henning, Remco van der Hofstad, Nelly Litvak
Based on observations in the web-graph, the power-law hypothesis states that PageRank has a power-law distribution with the same exponent as the in-degree. While this hypothesis ha…
Learning the mechanisms of network growth
Lourens Touwen, Doina Bucur, Remco van der Hofstad +2
We propose a novel model-selection method for dynamic networks. Our approach involves training a classifier on a large body of synthetic network data. The data is generated by simu…
The Projection Method: a Unified Formalism for Community Detection
Martijn Gösgens, Remco van der Hofstad, Nelly Litvak
We present the class of projection methods for community detection that generalizes many popular community detection methods. In this framework, we represent each clustering (parti…