Independent Component Analysis: Principles and Practice

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NICE: Non-linear Independent Components Estimation (2014, methodology): “t. A more principled proxy of log-likelihood, the variational lower bound, is used more successfully in nonlinear independent components analysis (Hyv¨arinen and Pajunen, 1999) via ensemble learning (Roberts and Everson, 2001; Lappalainen et al., 2000) and in (Kingma and Welling, 2014; Rezende et al”
Nonparametric independent component analysis (2004, methodology): “…form of the latent component densities pj and estimation of B together with parameters of pj using maximum likelihood or minimization of the empirical versions of various divergence criteria between densities; see Hyvärinen et al. (2001), Roberts and Everson (2001) and references therein.”
Advances in Nonlinear Blind Source Separation (2003, background): “This is referred to as the blind source separation (BSS) problem; blind since no or very little prior information about the sources is required.”