Publications of the Bayes group

This page contains a selection of our most important publications. There are also longer lists of recent publications and older publications. The figure shows the center of our campus area in Otaniemi, Espoo, Finland.

Variational Bayesian learning in general

A. Honkela, T. Raiko, M. Kuusela, M. Tornio, and J. Karhunen. Conjugate Gradient Learning for Fixed-Form Variational Bayes. In the Journal of Machine Learning Research (JMLR), 11(Nov):3235-3268, 2010.

T. Raiko, H. Valpola, M. Harva, J. Karhunen. (2007). Building blocks for variational Bayesian learning of latent variable models. Journal of Machine Learning Research 8(Jan), pp. 155-201.

A. Ilin, H. Valpola. (2005). On the Effect of the Form of the Posterior Approximation in Variational Learning of ICA Models. Neural Processing Letters 22(2), pp. 183-204.
doi:10.1007/s11063-005-5265-0

A. Honkela, H. Valpola. (2004). Variational learning and bits-back coding: an information-theoretic view to Bayesian learning. IEEE Transactions on Neural Networks 15(4), pp. 800-810.
doi:10.1109/TNN.2004.828762
Pdf (308k)

A. Honkela, H. Valpola, J. Karhunen. (2003). Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches. Neural Processing Letters 17(2), pp. 191-203.
doi:10.1023/A:1023655202546
Pdf (220k)

H. Lappalainen, J. Miskin. (2000). Ensemble Learning. In M. Girolami, editor, Advances in Independent Component Analysis, pp. 75-92, Springer-Verlag.
Gzipped postscript (127k)

PCA with sparse data

A. Ilin and T. Raiko. Practical Approaches to Principal Component Analysis in the Presence of Missing Values. In the Journal of Machine Learning Research (JMLR), volume 11, pages 1957-2000, July 2010.

Nonlinear dynamical models

T. Raiko and M. Tornio. Variational Bayesian learning of nonlinear hidden state-space models for model predictive control. In Neurocomputing, volume 72, issues 16-18, pages 3704-3712, October 2009.

A. Ilin, H. Valpola, E. Oja. (2004). Nonlinear Dynamical Factor Analysis for State Change Detection. IEEE Transactions on Neural Networks 15(3), pp. 559-575.
doi:10.1109/TNN.2004.826129

H. Valpola, J. Karhunen. (2002). An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models. Neural Computation 14(11), pp. 2647-2692.
Gzipped postscript (654k), Pdf (937k)

Variance modelling

H. Valpola, M. Harva, J. Karhunen. (2004). Hierarchical Models of Variance Sources. Signal Processing 84(2), pp. 267-282.
doi:10.1016/j.sigpro.2003.10.014
Pdf (1128k)

Nonlinear blind source separation and factor analysis

C. Jutten, M. Babaie-Zadeh, J. Karhunen. (2010). Nonlinear Mixtures. Chapter 14 in C. Jutten and P. Comon (editors), Handbook of Blind Source Separation, Independent Component Analysis and Applications, pp. 549-592, Academic Press.
Home page of the book

A. Honkela, H. Valpola, A. Ilin, J. Karhunen. (2007). Blind Separation of Nonlinear Mixtures by Variational Bayesian Learning. Digital Signal Processing 17(5), pp. 914-934.
doi:10.1016/j.dsp.2007.02.009
Pdf (1961k)

A. Honkela, H. Valpola. (2005). Unsupervised Variational Bayesian Learning of Nonlinear Models. In L. Saul, Y. Weiss, L. Bottou, editors, Advances in Neural Information Processing Systems 17, pp. 593-600, MIT Press.
Pdf (118k)

H. Lappalainen, A. Honkela. (2000). Bayesian Nonlinear Independent Component Analysis by Multi-Layer Perceptrons. In M. Girolami, editor, Advances in Independent Component Analysis, pp. 93-121, Springer-Verlag.
Gzipped postscript (420k), Pdf (991k)

Nonnegative independent component analysis

M. Harva, A. Kabán. (2007). Variational Learning for Rectified Factor Analysis. Signal Processing 87(3), pp. 509-527.
doi:10.1016/j.sigpro.2006.06.006
Pdf (655k)

Relational models

K. Kersting, L. D. Raedt, T. Raiko. (2006). Logical Hidden Markov Models. Journal of Artificial Intelligence Research 25(), pp. 425-456.
Publisher electronic edition

Applications

L. Nolan, M. Harva, A. Kabán, S. Raychaudhury. (2006). A data-driven Bayesian approach for finding young stellar populations in early-type galaxies from their UV-optical spectra. Monthly Notices of the Royal Astronomical Society 366(1), pp. 321-338.
doi:10.1111/j.1365-2966.2005.09868.x
Gzipped postscript (279k)

Theses

T. Raiko. (2006). Bayesian Inference in Nonlinear and Relational Latent Variable Models. PhD thesis, Helsinki University of Technology, Espoo, Finland.
Electronic dissertation

A. Ilin. (2006). Advanced Source Separation Methods with Applications to Spatio-Temporal Datasets. PhD thesis, Helsinki University of Technology, Espoo, Finland.
Electronic dissertation

A. Honkela. (2005). Advances in Variational Bayesian Nonlinear Blind Source Separation. PhD thesis, Helsinki University of Technology, Espoo, Finland.
Electronic dissertation

H. Valpola. (2000). Bayesian Ensemble Learning for Nonlinear Factor Analysis. PhD thesis, Helsinki University of Technology, Espoo, Finland. Published in Acta Polytechnica Scandinavica, Mathematics and Computing Series No. 108.
Pdf (3414k)

M. Harva. (2004). Hierarchical Variance Models of Image Sequences. Master's thesis, Helsinki University of Technology, Espoo.
Gzipped postscript (926k), Pdf (893k)

T. Raiko. (2001). Hierarchical Nonlinear Factor Analysis. Master's thesis, Helsinki University of Technology, Espoo, Finland.
Gzipped postscript (495k), Pdf (1035k)

A. Honkela. (2001). Nonlinear Switching State-Space Models. Master's thesis, Helsinki University of Technology, Espoo.
Gzipped postscript (658k), Pdf (843k)