Dynamic Mixed Membership Stochastic Block Model for Weighted Labeled Networks

Author:

Poux-Médard Gaël1ORCID,Velcin Julien1ORCID,Loudcher Sabine1ORCID

Affiliation:

1. Université de Lyon, Lyon 2, UR 3083, Lyon, France

Publisher

ACM

Reference35 articles.

1. Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model. Proc. 11th Conf. on;Ahmed Amr;Art. Int. and Stat.,2007

2. Edoardo M. Airoldi , David M. Blei , Stephen E. Fienberg , and Eric P . Xing . 2008 . Mixed Membership Stochastic Blockmodels. J. Mach. Learn. Res . 9 (jun 2008), 1981--2014. https://dl.acm.org/doi/10.5555/1390681.1442798 Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, and Eric P. Xing. 2008. Mixed Membership Stochastic Blockmodels. J. Mach. Learn. Res. 9 (jun 2008), 1981--2014. https://dl.acm.org/doi/10.5555/1390681.1442798

3. Poisson Process Approximations for the Ewens Sampling Formula

4. Christopher Bishop . 2006. Pattern Recognition and Machine Learning . Springer . 450--455 pages. Christopher Bishop. 2006. Pattern Recognition and Machine Learning. Springer. 450--455 pages.

5. S. Cobo-López A. Godoy-Lorite and J. Duch. 2018. Optimal prediction of decisions and model selection in social dilemmas using block models. EPJ Data Sci 7

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