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Volumn 3, Issue , 2018, Pages 1749-1760

Inference suboptimality in variational autoencoders

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPLEX NETWORKS;

EID: 85057248218     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (134)

References (32)
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    • Geweke, J.1
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    • Learning deep latent Gaussian models with markov chain monte carlo
    • Hoffman, Matthew D. Learning deep latent gaussian models with markov chain monte carlo. In International Conference on Machine Learning, pp. 1510-1519, 2017.
    • (2017) International Conference on Machine Learning , pp. 1510-1519
    • Hoffman, M.D.1
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    • 4243754128 scopus 로고    scopus 로고
    • Nonequilibrium equality for free energy differences
    • Jarzynski, C. Nonequilibrium equality for free energy differences. Physical Review Letters, 78(14):2690, 1997.
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    • Jarzynski, C.1
  • 14
    • 85083952489 scopus 로고    scopus 로고
    • Auto-encoding variational bayes
    • Kingma, D.P. and Welling, M. Auto-Encoding Variational Bayes. In ICLR, 2014.
    • (2014) ICLR
    • Kingma, D.P.1    Welling, M.2
  • 23
    • 84969776493 scopus 로고    scopus 로고
    • Variational inference with normalizing flows
    • Rezende, D.J. and Mohamed, S. Variational Inference with Normalizing Flows. In ICML, 2015.
    • (2015) ICML
    • Rezende, D.J.1    Mohamed, S.2
  • 24
    • 84919796093 scopus 로고    scopus 로고
    • Stochastic backpropagation and approximate inference in deep generative models
    • Rezende, D.J., Mohamed, S., and Wierstra, D. Stochastic Backpropagation and Approximate Inference in Deep Generative Models. ICML, 2014.
    • (2014) ICML
    • Rezende, D.J.1    Mohamed, S.2    Wierstra, D.3
  • 26
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    • Markov chain monte carlo and variational inference: Bridging the gap
    • Salimans, T., Kingma, D.P., and Welling, M. Markov chain monte carlo and variational inference: Bridging the gap. In ICML, 2015.
    • (2015) ICML
    • Salimans, T.1    Kingma, D.P.2    Welling, M.3
  • 31
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    • On the quantitative analysis of decoder-based generative models
    • Wu, Y., Burda, Y., Salakhutdinov, R., and Grosse, R. On the Quantitative Analysis of Decoder-Based Generative Models. ICLR, 2017.
    • (2017) ICLR
    • Wu, Y.1    Burda, Y.2    Salakhutdinov, R.3    Grosse, R.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.