FastICA is made robust to unknown source distributions by learning the required nonlinear function from the empirical characteristic function of the mixtures.
On the determination of probability distributions of more dimensions by their projections,
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FastICA with Learned Scores from the Empirical Characteristic Function
FastICA is made robust to unknown source distributions by learning the required nonlinear function from the empirical characteristic function of the mixtures.