most citedDisentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA

21 citations · 21 across the 1 of their papers we have counts for

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stat.ML2021★ 21 cited

Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA

Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy +4

We introduce a new general identifiable framework for principled disentanglement referred to as Structured Nonlinear Independent Component Analysis (SNICA). Our contribution is to…