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Activity Number:
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333
- Recent Developments in Network Inference Methods
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Type:
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Invited
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Date/Time:
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Thursday, August 12, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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IMS
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Abstract #315553
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Title:
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Identifying Heterogeneous Temporal Structure from Multiple Network Time Series
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Author(s):
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Carey E Priebe* and Guodong Chen and Jonathan Larson and Weiwei Yang and Christopher White and Joshua Vogelstein and Youngser Park
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Companies:
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Johns Hopkins University and Johns Hopkins University and Microsoft Research and Mocrosoft Research and Microsoft Research and Johns Hopkins University and Johns Hopkins University
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Keywords:
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Abstract:
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Modeling and characterizing time series of graphs is an important and challenging task with myriad applications throughout network science. Here, we consider a collection of time series of behavioral networks $\{G_t^m\}$ for series $m \in [M]$ and times $t \in [T]$. A common exogenous event impacts these networks, but the structural effect may be different for different series. We explore inferential methods for identifying individual network properties implicated in such differential effects.
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Authors who are presenting talks have a * after their name.
