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Volumn 2015-January, Issue , 2015, Pages 568-576

Automatic variational inference in Stan

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; FACTORIZATION; INFORMATION SCIENCE; MIXTURES;

EID: 84965158671     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (171)

References (25)
  • 1
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    • (1999) Machine Learning , vol.37 , Issue.2 , pp. 183-233
    • Jordan, M.I.1    Ghahramani, Z.2    Jaakkola, T.S.3    Saul, L.K.4
  • 2
    • 65749118363 scopus 로고    scopus 로고
    • Graphical models, exponential families, and variational inference
    • Martin J Wainwright and Michael I Jordan. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1(1-2):1-305, 2008.
    • (2008) Foundations and Trends in Machine Learning , vol.1 , Issue.1-2 , pp. 1-305
    • Wainwright, M.J.1    Jordan, M.I.2
  • 7
    • 84919796093 scopus 로고    scopus 로고
    • Stochastic backpropagation and approximate inference in deep generative models
    • Danilo J Rezende, Shakir Mohamed, and Daan Wierstra. Stochastic backpropagation and approximate inference in deep generative models. In ICML, pages 1278-1286, 2014.
    • (2014) ICML , pp. 1278-1286
    • Rezende, D.J.1    Mohamed, S.2    Wierstra, D.3
  • 8
    • 84955506831 scopus 로고    scopus 로고
    • Black box variational inference
    • Rajesh Ranganath, Sean Gerrish, and David Blei. Black box variational inference. In AISTATS, pages 814-822, 2014.
    • (2014) AISTATS , pp. 814-822
    • Ranganath, R.1    Gerrish, S.2    Blei, D.3
  • 10
    • 84919786928 scopus 로고    scopus 로고
    • Doubly stochastic variational Bayes for nonconjugate inference
    • Michalis Titsias and Miguel Lázaro-Gredilla. Doubly stochastic variational Bayes for nonconjugate inference. In ICML, pages 1971-1979, 2014.
    • (2014) ICML , pp. 1971-1979
    • Titsias, M.1    Lázaro-Gredilla, M.2
  • 14
    • 84959183806 scopus 로고    scopus 로고
    • A new approach to probabilistic programming inference
    • Frank Wood, Jan Willem van de Meent, and Vikash Mansinghka. A new approach to probabilistic programming inference. In AISTATS, pages 2-46, 2014.
    • (2014) AISTATS , pp. 2-46
    • Wood, F.1    Willem Van De Meent, J.2    Mansinghka, V.3
  • 18
    • 63249135864 scopus 로고    scopus 로고
    • The variational Gaussian approximation revisited
    • Manfred Opper and Cédric Archambeau. The variational Gaussian approximation revisited. Neural computation, 21(3):786-792, 2009.
    • (2009) Neural Computation , vol.21 , Issue.3 , pp. 786-792
    • Opper, M.1    Archambeau, C.2
  • 21
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgradient methods for online learning and stochastic optimization
    • John Duchi, Elad Hazan, and Yoram Singer. Adaptive subgradient methods for online learning and stochastic optimization. The Journal of Machine Learning Research, 12:2121-2159, 2011.
    • (2011) The Journal of Machine Learning Research , vol.12 , pp. 2121-2159
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
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    • GaP: A factor model for discrete data
    • ACM
    • John Canny. GaP: a factor model for discrete data. In ACM SIGIR, pages 122-129. ACM, 2004.
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    • Canny, J.1
  • 25


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.