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Found 4 papers, 1 papers with code
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
A topic of great current interest is Causal Representation Learning (CRL), whose goal is to learn a causal model for hidden features in a data-driven manner.
Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning
A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called "disentanglement".
Independent Innovation Analysis for Nonlinear Vector Autoregressive Process
Additivity greatly limits the generality of the model, hindering analysis of general NVAR processes which have nonlinear interactions between the innovations.
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA
Nonlinear independent component analysis (ICA) provides an appealing framework for unsupervised feature learning, but the models proposed so far are not identifiable.
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