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cs.LG2025
Physics-Informed Learning of Flow Distribution and Receiver Heat Losses in Parabolic Trough Solar Fields
Stefan Matthes, Markus Schramm
Parabolic trough Concentrating Solar Power (CSP) plants operate large hydraulic networks of collector loops that must deliver a uniform outlet temperature despite spatially heterog…
cs.LG2025
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.LG2025
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…