Bibliography

1

G. E. Hinton and D. van Camp, ``Keeping neural networks simple by minimizing the description length of the weights,'' in Proc. COLT'93, pp. 5-13, 1993.

2

H. Attias, ``Independent factor analysis,'' Neural Computation, vol. 11, no. 4, pp. 803-851, 1999.

3

B. J. Frey and G. E. Hinton, ``Variational learning in nonlinear gaussian belief networks,'' Neural Computation, vol. 11, no. 1, pp. 193-214, 1999.

4

K. P. Murphy, ``A variational approximation for Bayesian networks with discrete and continuous latent variables,'' In Proc. UAI-99, pp. 457-466, 1999.

5

H. Lappalainen and A. Honkela, ``Bayesian nonlinear independent component analysis by multi-layer perceptrons,'' in Advances in Independent Component Analysis (M. Girolami, ed.), pp. 93-121, Springer-Verlag, 2000.

6

H. Valpola, ``Unsupervised learning of nonlinear dynamic state-space models,'' Publications in Computer and Information Science A59, Helsinki University of Technology, Espoo, Finland, 2000.

7

T. Kohonen, S. Kaski, and H. Lappalainen, ``Self-organized formation of various invariant-feature filters in the Adaptive-Subspace SOM,'' Neural Computation, vol. 9, no. 6, pp. 1321-1344, 1997.

8

J.-F. Cardoso, ``Multidimensional independent component analysis,'' In Proc. ICASSP'98, pp. 1941-1944, 1998.

9

D.-T. Pham and J.-F. Cardoso, ``Blind separation of instantaneous mixtures of non stationary sources,'' In Proc. ICA 2000, pp. 187-192, 2000.

10

Z. Ghahramani and G. E. Hinton, ``Hierarchical non-linear factor analysis and topographic maps,'' In Adv. in Neur. Inf. Proc. Syst. 10, NIPS*97, pp. 486-492, 1998.

11

A. Hyvärinen and P. O. Hoyer, ``Emergence of topography and complex cell properties from natural images using extensions of ICA,'' In Adv. in Neur. Inf. Proc. Syst. 12, NIPS*99, pp. 827-833, 2000.

12

A. Hyvärinen and P. O. Hoyer, ``Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces,'' Neural Computation, vol. 12, no. 7, pp. 1705-1720, 2000.

13

M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul, ``An introduction to variational methods for graphical models,'' in Learning in Graphical Models (M. I. Jordan, ed.), pp. 105-161, The MIT Press, 1999.

14

H. Lappalainen and J. W. Miskin, ``Ensemble learning,'' in Advances in Independent Component Analysis (M. Girolami, ed.), pp. 76-92, Springer-Verlag, 2000.

15

Z. Ghahramani and S. T. Roweis, ``Learning nonlinear dynamical systems using an EM algorithm,'' In Adv. in Neur. Inf. Proc. Syst. 11, NIPS*98, pp. 599-605, 1999.

16

P. Dayan and R. S. Zemel, ``Competition and multiple cause models,'' Neural Computation, vol. 7, no. 3, pp. 565-579, 1995.