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Elisabeth Gassiat

1 accepted papers

2021

Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA

NeurIPS 2021poster

We introduce a new general identifiable framework for principled disentanglement referred to as Structured Nonlinear Independent Component Analysis (SNICA). Our contribution is to extend the identifiability theory of deep generative models for a very broad class of structured models. While previous…