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20162026
most citedCorrelated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities

13 citations · 17 across the 8 of their papers we have counts for

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8 papers · 1 filter

math.ST2026

Finding Super-spreaders in SIS Epidemics

Anirudh Sridhar, Arnob Ghosh

In network epidemic models, controlling the spread of a disease often requires targeted interventions such as vaccinating high-risk individuals based on network structure. However,…

math.ST2026

Detecting Mutual Excitations in Non-Stationary Hawkes Processes

Elchanan Mossel, Anirudh Sridhar

We consider the problem of learning the network of mutual excitations (i.e., the dependency graph) in a non-stationary, multivariate Hawkes process. We consider a general setting w…

math.ST2025

Detecting Abrupt Changes in Point Processes: Fundamental Limits and Applications

Anna Brandenberger, Elchanan Mossel, Anirudh Sridhar

We consider the problem of detecting abrupt changes (i.e., large jump discontinuities) in the rate function of a point process. The rate function is assumed to be fully unknown, no…

math.ST2024

Finding Super-spreaders in Network Cascades

Elchanan Mossel, Anirudh Sridhar

Suppose that a cascade (e.g., an epidemic) spreads on an unknown graph, and only the infection times of vertices are observed. What can be learned about the graph from the infectio…

math.ST20223 cited

Exact Community Recovery in Correlated Stochastic Block Models

Julia Gaudio, Miklos Z. Racz, Anirudh Sridhar

We consider the problem of learning latent community structure from multiple correlated networks. We study edge-correlated stochastic block models with two balanced communities, fo…

math.ST202113 cited

Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities

Miklos Z. Racz, Anirudh Sridhar

We consider the task of learning latent community structure from multiple correlated networks. First, we study the problem of learning the latent vertex correspondence between two…