3 papers
cs.LG2026
Provable Subspace Identification of Nonlinear Multi-view CCA
Zhiwei Han, Stefan Matthes, Hao Shen
We investigate the identifiability of nonlinear canonical correlation analysis (CCA) in a multi-view setup, in which each view is generated by applying an unknown nonlinear map to…
cs.LG2026
Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors
Zhiwei Han, Stefan Matthes, Hao Shen
In this work, we establish the sufficient conditions under which nonlinear Canonical Correlation Analysis (CCA) recovers ground-truth latent factors up to an affine transformation.…
cs.LG2026
Mechanistic Independence: A Principle for Identifiable Disentangled Representations
Stefan Matthes, Zhiwei Han, Hao Shen
Disentangled representations seek to recover latent factors of variation underlying observed data, yet their identifiability is still not fully understood. We introduce a unified f…