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Volumn , Issue , 2006, Pages 155-162

Estimation of linear, non-gaussian causal models in the presence of confounding latent variables

Author keywords

[No Author keywords available]

Indexed keywords

CAUSAL MODEL; FINITE SET; GAUSSIANITY; HIDDEN VARIABLE; IDENTIFIABILITY; LATENT VARIABLE; LINEAR CAUSAL MODELS; MATLAB CODE; NON-GAUSSIAN; NON-GAUSSIAN DISTRIBUTION; STRUCTURAL EQUATION MODELS; THEORETICAL ARGUMENTS;

EID: 33749343571     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (14)

References (13)
  • 1
    • 0033561886 scopus 로고    scopus 로고
    • Independent factor analysis
    • H. Attias. 1999. Independent factor analysis. Neural Computation, 11:803-851.
    • (1999) Neural Computation , vol.11 , pp. 803-851
    • Attias, H.1
  • 3
    • 0028416938 scopus 로고
    • Independent component analysis-a new concept?
    • P. Comon. 1994. Independent component analysis-a new concept? Signal Processing, 36:287-314.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 5
    • 3142743269 scopus 로고    scopus 로고
    • Identifiability, separability and uniqueness of linear ICA models
    • J. Eriksson and V. Koivunen. 2004. Identifiability, separability and uniqueness of linear ICA models. IEEE Signal Processing Letters, ll(7):601-604.
    • (2004) IEEE Signal Processing Letters , vol.11 , Issue.7 , pp. 601-604
    • Eriksson, J.1    Koivunen, V.2
  • 7
    • 0034222304 scopus 로고    scopus 로고
    • Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces
    • A. Hyvärinen and P. O. Hoyer. 2000. Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces. Neural Computation, 12(7):1705-1720.
    • (2000) Neural Computation , vol.12 , Issue.7 , pp. 1705-1720
    • Hyvärinen, A.1    Hoyer, P.O.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.