Dynamic mixed membership blockmodel for evolving networks

By Wenjie Fu, Le Song, Eric P. Xing. 2009

185 citations recorded by the source corpus.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Aram Galstyan
2. Philip S. Yu
3. David Mimno
4. Greg Ver Steeg
5. David M. Blei
6. Junming Yin
7. Dong Guo
8. Sean Gerrish

In Statistical and Nonlinear Physics

1. Prem Gopalan
2. Philip S. Yu
3. David M. Blei
4. Aram Galstyan
5. David Mimno
6. Greg Ver Steeg
7. Junming Yin
8. Dong Guo

Citations in the corpus

• Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (2014, methodology): “[39], local optimization approaches NMFR [40], Hott [28],”
• A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning (2021, background): “[53] design a state space mixed membership stochastic block model with crossing time.”
• Scalable Inference of Overlapping Communities (2012, background): “The MMSB can capture complex community structure and has been adapted in several ways [11, 12]; however, its applications have been limited because its corresponding inference algorithms have not scaled to large networks [2].”