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Unsupervised Variational Bayesian Learning of Nonlinear Models., and . NIPS, page 593-600. (2004)Denoising Source Separation., and . J. Mach. Learn. Res., (2005)Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method., , , and . ICA, volume 3195 of Lecture Notes in Computer Science, page 790-797. Springer, (2004)Pushing Stochastic Gradient towards Second-Order Methods - Backpropagation Learning with Transformations in Nonlinearities., , , and . ICONIP (1), volume 8226 of Lecture Notes in Computer Science, page 442-449. Springer, (2013)Building Blocks for Variational Bayesian Learning of Latent Variable Models., , , and . J. Mach. Learn. Res., (2007)On the exact relationship between the denoising function and the data distribution., , and . CoRR, (2017)Development of Representations, Categories and Concepts - a Hypothesis.. CIRA, page 593-599. IEEE, (2005)Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results., and . NIPS, page 1195-1204. (2017)Deep Learning Made Easier by Linear Transformations in Perceptrons., , and . AISTATS, volume 22 of JMLR Proceedings, page 924-932. JMLR.org, (2012)Hierarchical models of variance sources., , and . Signal Process., 84 (2): 267-282 (2004)