Z. Ghahramani and G. E. Hinton, The EM Algorithm for Mixtures of Factor Analyzers, Canada, 1996.

T. Kohonen, Self-Organizing Maps. Springer Series in Information Sciences, 2001.

R. M. Neal and G. E. Hinton, A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants, Learning in Graphical Models, pp.355-368, 1998.
DOI : 10.1007/978-94-011-5014-9_12

S. T. Roweis, L. K. Saul, and G. E. Hinton, Global coordination of local linear models, Advances in Neural Information Processing Systems 14, 2002.

J. B. Tenenbaum, V. De-silva, and J. C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, vol.290, issue.5500, pp.2902319-2323, 2000.
DOI : 10.1126/science.290.5500.2319

M. E. Tipping and C. M. Bishop, Mixtures of Probabilistic Principal Component Analyzers, Neural Computation, vol.2, issue.1, pp.443-482, 1999.
DOI : 10.1007/BF00162527

J. J. Verbeek, N. Vlassis, and B. Kröse, The Generative Self-Organizing Map: A Probabilistic Generalization of Kohonen's SOM, 2002.

J. J. Verbeek, N. Vlassis, and B. Kröse, Procrustes Analysis to Coordinate Mixtures of Probabilistic Principal Component Analyzers, 2002.
URL : https://hal.archives-ouvertes.fr/inria-00321503

N. Vlassis, Y. Motomura, and B. Kröse, Supervised Dimension Reduction of Intrinsically Low-Dimensional Data, Neural Computation, vol.39, issue.1, pp.191-215, 2002.
DOI : 10.1214/aos/1176343886