Events Archive

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Zoom access to the talks:
https://uni-frankfurt.zoom.us/j/91292915620?pwd=QkR5THI0MklWWDR1ajBoUytFOXBwUT09

Meeting-ID: 912 9291 5620
Code: 109618
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Programme for 29 January 2021 (times are CET):

15:15-16:15 Gábor Lugosi  (Pompeu Fabra University, Barcelona)

16:15-16:45 virtual coffee break (tba)

16:45-17:45 Po-Ling Loh (University of Cambridge)

The seminar takes place online via zoom.
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Gábor Lugosi  (Pompeu Fabra University, Barcelona)

Title: Root finding and broadcasting in random recursive trees

Abstract: Uniform and preferential attachment trees are among the simplest examples of dynamically growing networks. The statistical problems we address in this talk regard discovering the past of the tree when a present-day snapshot is observed. We present a few results that show that, even in gigantic networks, a lot of information is preserved from the very early days. In particular, we discuss the problem of finding the root and the broadcasting problem.


Po-Ling Loh (University of Cambridge)

Title: Statistical inference for infectious disease modeling

Abstract: We discuss two recent results concerning disease modeling on networks. The infection is assumed to spread via contagion (e.g., transmission over the edges of an underlying network). In the first scenario, we observe the infection status of individuals at a particular time instance and the goal is to identify a confidence set of nodes that contain the source of the infection with high probability. We show that when the underlying graph is a tree with certain regularity properties and the structure of the graph is known, confidence sets may be constructed with cardinality independent of the size of the infection set. Furthermore, we prove that the confidence sets are almost surely persistent, i.e., they settle down after a finite number of time steps. In the second scenario, the goal is to infer the network structure of the underlying graph based on knowledge of the infected individuals. We develop a hypothesis test based on permutation testing, and describe a sufficient condition for the validity of the hypothesis test based on automorphism groups of the graphs involved in the hypothesis test.

This is joint work with Justin Khim and Varun Jog.