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cs.LG2026
Causal Representation Learning with Instantaneous and Lagged Relations via Nonstationarity
Tatsuya Yamada, Hiroshi Morioka, Yoshinobu Kawahara
Causal representation learning for time-series data aims to identify latent states and their causal relations from observations. In this setting, an important challenge is to model…
cs.LG2023★ 3 cited
Nonlinear Independent Component Analysis for Principled Disentanglement in Unsupervised Deep Learning
Aapo Hyvarinen, Ilyes Khemakhem, Hiroshi Morioka
A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called "disentanglement". Most approaches are heuristic an…