Bayesian variational inference for exponential random graph models

10.1080/10618600.2020.1740714

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Bibliographic Details
Main Authors: Linda Siew Li Tan, Nial Friel
Other Authors: STATISTICS & APPLIED PROBABILITY
Format: Article
Published: Taylor & Francis 2021
Online Access:https://scholarbank.nus.edu.sg/handle/10635/185602
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Institution: National University of Singapore
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spelling sg-nus-scholar.10635-1856022024-04-03T05:45:57Z Bayesian variational inference for exponential random graph models Linda Siew Li Tan Nial Friel STATISTICS & APPLIED PROBABILITY 10.1080/10618600.2020.1740714 Journal of Computational and Graphical Statistics 29 04 910-928 2021-01-18T07:07:51Z 2021-01-18T07:07:51Z 2020-04-15 Article Linda Siew Li Tan, Nial Friel (2020-04-15). Bayesian variational inference for exponential random graph models. Journal of Computational and Graphical Statistics 29 (04) : 910-928. ScholarBank@NUS Repository. https://doi.org/10.1080/10618600.2020.1740714 10618600 https://scholarbank.nus.edu.sg/handle/10635/185602 Taylor & Francis Taylor & Francis
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
description 10.1080/10618600.2020.1740714
author2 STATISTICS & APPLIED PROBABILITY
author_facet STATISTICS & APPLIED PROBABILITY
Linda Siew Li Tan
Nial Friel
format Article
author Linda Siew Li Tan
Nial Friel
spellingShingle Linda Siew Li Tan
Nial Friel
Bayesian variational inference for exponential random graph models
author_sort Linda Siew Li Tan
title Bayesian variational inference for exponential random graph models
title_short Bayesian variational inference for exponential random graph models
title_full Bayesian variational inference for exponential random graph models
title_fullStr Bayesian variational inference for exponential random graph models
title_full_unstemmed Bayesian variational inference for exponential random graph models
title_sort bayesian variational inference for exponential random graph models
publisher Taylor & Francis
publishDate 2021
url https://scholarbank.nus.edu.sg/handle/10635/185602
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