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Theses done in the research group

Doctoral Theses


M. Berglund (2017). Unsupervised Networks, Stochasticity and Optimization in Deep Learning. PhD thesis, Aalto University, Department of Computer Science, Espoo, Finland, April 2017.

J. Luttinen (2015). Bayesian Latent Gaussian Spatio-Temporal Models. PhD thesis, Aalto University, Espoo, Finland.

K. Cho (2014). Foundations and Advances in Deep Learning. PhD thesis, Aalto University, Espoo, Finland.

M. Harva (2008). Algorithms for Approximate Bayesian Inference with Applications to Astronomical Data Analysis. PhD thesis, Helsinki University of Technology, Espoo, Finland.

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

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

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

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.

Master's Theses


G. van den Broeke (2016). What auto-encoders could learn from brains - Generation as feedback in unsupervised deep learning and inference. Master's thesis, Aalto University, Helsinki, Finland.

M. Perello Nieto (2015). Merging chrominance and luminance in an early, medium and late fusion using Convolutional Neural Networks. Master's thesis, Aalto University, Helsinki, Finland.

T. Hao (2012). Gated Boltzmann Machine in Texture Modelling. Master's thesis, Aalto University, Helsinki, Finland.

K. Cho (2011). Improved Learning Algorithms for Restricted Boltzmann Machines. Master's thesis, Aalto University, Helsinki, Finland.

M. Tornio (2010). Natural Gradient for Variational Bayesian Learning. Master's thesis, Aalto University, Helsinki, Finland.

J. Luttinen (2009). Gaussian-process factor analysis for modeling spatio-temporal data. Master's thesis, Helsinki University of Technology, Espoo, Finland.

M. Harva (2004). Hierarchical Variance Models of Image Sequences. Master's thesis, Helsinki University of Technology, Espoo, Finland.

T. Raiko (2001). Hierarchical Nonlinear Factor Analysis. Master's thesis, Helsinki University of Technology, Espoo, Finland.

A. Honkela (2001). Nonlinear Switching State-Space Models. Master's thesis, Helsinki University of Technology, Espoo, Finland.