University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Bayesian ERGMs -- computational and modelling challenges

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Bayesian ERGMs -- computational and modelling challenges

Download to your calendar using vCal

If you have a question about this talk, please contact INI IT .

SNA - Theoretical foundations for statistical network analysis

Recent research in statistical social network analysis has demonstrated the advantages and effectiveness of Bayesian approaches to network data. In fact, Bayesian exponential random graph models (BERGMs) are becoming increasingly popular as techniques for modelling relational data in wide range of research areas. However, the applicability of these models in real-world settings is limited by computational complexity. In this seminar we review some of the most recent computational methods for estimating BERG Ms as well as extended ERGM -based modelling frameworks for dynamic and heterogenous social networks.

This talk is part of the Isaac Newton Institute Seminar Series series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Average on weekdays: 8973.62867647 kWh MR13 Centre for Mathematical Sciences Cambridge University Engineering Department,LR 3A

Other talks

Talk title TBC Cooperation for Nature Title to be confirmed Title to be confirmed Cambridge Reading Group on Reproduction: Professor Sara Brill Scientific Steering Committee meeting
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity