We consider the problem of estimating the location of a single change point in a network
generated by a dynamic stochastic block model mechanism. This model produces …

We propose a dynamic network model where two mechanisms control the probability of a
link between two nodes:(i) the existence or absence of this link in the past, and (ii) node …

Dynamic network models and graphon estimation Page 1 The Annals of Statistics 2019, Vol.
47, No. 4, 2378–2403 https://doi.org/10.1214/18-AOS1751 © Institute of Mathematical …

We propose a first-order autoregressive (ie AR (1)) model for dynamic network processes in
which edges change over time while nodes remain unchanged. The model depicts the …

The increasing amount of data stored in the form of dynamic interactions between actors
necessitates the use of methodologies to automatically extract relevant information. The …

Graphs provide a powerful framework to represent high-dimensional but structured data,
and to make inferences about relationships between subsets of the data. In this work we …

Networks have become indispensable and ubiquitous structures in many fields to model the
interactions among different entities, such as friendship in social networks or protein …

A new class of models for dynamic networks is proposed, called mutually exciting point
process graphs (MEG). MEG is a scalable network-wide statistical model for point processes …

The mutually-exciting Hawkes process (ME-HP) is a natural choice to model reciprocity,
which is an important attribute of continuous-time edge (dyadic) data. However, existing …

The problem of anomaly detection in time series of graphs is considered, focusing on two
related inference tasks: the detection of anomalous graphs within a time series and the …