This page contains a selection of our most important publications. There is also a complete listing.
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.
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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.
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M. Harva, T. Raiko, A. Honkela, H. Valpola, J. Karhunen. (2005). Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. In Proc. of the 21st Conf. on Uncertainty in Artificial Intelligence (UAI 2005), Edinburgh, Scotland, pp. 259-266.
Gzipped postscript (235k), Pdf (164k)
H. Valpola, J. Karhunen. (2002). An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models. Neural Computation 14(11), pp. 2647-2692.
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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
T. Raiko, M. Tornio, A. Honkela, J. Karhunen. (2006). State Inference in Variational Bayesian Nonlinear State-Space Models. In Proceedings of the 6th International Conference on Independent Component Analysis and Blind Source Separation (ICA 2006), Charleston, South Carolina, USA, pp. 222-229.
Pdf (152k)
J. Särelä, H. Valpola, R. Vigário, E. Oja. (2001). Dynamical Factor Analysis of Rhythmic Magnetoencephalographic Activity. In Proc. Int. Conf. on Independent Component Analysis and Signal Separation (ICA2001), San Diego, USA, pp. 451-456.
Pdf (468k)
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)
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)
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)
H. Valpola, P. Pajunen. (2000). Fast Algorithms for Bayesian Independent Component Analysis. In Proc. Int. Workshop on Independent Component Analysis and Blind Signal Separation (ICA2000), Helsinki, Finland, pp. 233-237.
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H. Lappalainen. (1999). Ensemble learning for independent component analysis. In Proc. Int. Workshop on Independent Component Analysis and Signal Separation (ICA'99), Aussois, France, pp. 7-12.
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K. Kersting, L. D. Raedt, T. Raiko. (2006). Logical Hidden Markov Models. Journal of Artificial Intelligence Research 25(), pp. 425-456.
Publisher electronic edition
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
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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.
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M. Harva. (2004). Hierarchical Variance Models of Image Sequences. Master's thesis, Helsinki University of Technology, Espoo.
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T. Raiko. (2001). Hierarchical Nonlinear Factor Analysis. Master's thesis, Helsinki University of Technology, Espoo, Finland.
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A. Honkela. (2001). Nonlinear Switching State-Space Models. Master's thesis, Helsinki University of Technology, Espoo.
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