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Volumn , Issue , 2005, Pages

Unsupervised variational bayesian learning of nonlinear models

Author keywords

[No Author keywords available]

Indexed keywords

GAUSS-HERMITE QUADRATURE; GENERATIVE MODEL; INDEPENDENT COMPONENTS; LINEAR ALGORITHMS; NON-LINEAR MODEL; NONLINEAR FACTOR ANALYSIS; STATE-SPACE MODELS; VARIATIONAL BAYESIAN LEARNING;

EID: 27844480834     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (31)

References (14)
  • 6
    • 0002144623 scopus 로고    scopus 로고
    • Bayesian nonlinear independent component analysis by multi-layer perceptrons
    • Springer-Verlag, Berlin
    • H. Lappalainen and A. Honkela. Bayesian nonlinear independent component analysis by multi-layer perceptrons. In M. Girolami, ed., Advances in Independent Component Analysis, pp. 93-121. Springer-Verlag, Berlin, 2000.
    • (2000) M. Girolami, Ed., Advances in Independent Component Analysis , pp. 93-121
    • Lappalainen, H.1    Honkela, A.2
  • 8
    • 0033561886 scopus 로고    scopus 로고
    • Independent factor analysis
    • H. Attias. Independent factor analysis. Neural Computation, 11(4):803-851, 1999.
    • (1999) Neural Computation , vol.11 , Issue.4 , pp. 803-851
    • Attias, H.1
  • 9
    • 0038132747 scopus 로고    scopus 로고
    • An unsupervised ensemble learning method for nonlinear dynamic state-space models
    • H. Valpola and J. Karhunen. An unsupervised ensemble learning method for nonlinear dynamic state-space models. Neural Computation, 14(11):2647-2692, 2002.
    • (2002) Neural Computation , vol.14 , Issue.11 , pp. 2647-2692
    • Valpola, H.1    Karhunen, J.2
  • 10
    • 84898964031 scopus 로고    scopus 로고
    • A variational bayesian framework for graphical models
    • MIT Press
    • H. Attias. A variational Bayesian framework for graphical models. In Advances in Neural Information Processing Systems 12, pp. 209-215. MIT Press, 2000.
    • (2000) Advances in Neural Information Processing Systems , vol.12 , pp. 209-215
    • Attias, H.1
  • 11
    • 84899003086 scopus 로고    scopus 로고
    • Propagation algorithms for variational bayesian learning
    • s, MIT Press
    • Z. Ghahramani and M. Beal. Propagation algorithms for variational Bayesian learning. In Advances in Neural Information Processing Systems 13, pp. 507-513. MIT Press, 2001.
    • (2001) Advances in Neural Information Processing System , vol.13 , pp. 507-513
    • Ghahramani, Z.1    Beal, M.2
  • 12
    • 10844294195 scopus 로고    scopus 로고
    • Approximating nonlinear transformations of probability distributions for nonlinear independent component analysis
    • Budapest, Hungary
    • A. Honkela. Approximating nonlinear transformations of probability distributions for nonlinear independent component analysis. In Proc. 2004 IEEE Int. Joint Conf. on Neural Networks (IJCNN 2004), pp. 2169-2174, Budapest, Hungary, 2004.
    • (2004) Proc. 2004 IEEE Int. Joint Conf. on Neural Networks (IJCNN 2004) , pp. 2169-2174
    • Honkela, A.1
  • 14
    • 0001596032 scopus 로고    scopus 로고
    • Delayed curse of dimension for gaussian integration
    • F. Curbera. Delayed curse of dimension for Gaussian integration. Journal of Complexity, 16(2):474-506, 2000.
    • (2000) Journal of Complexity , vol.16 , Issue.2 , pp. 474-506
    • Curbera, F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.