arXiv Machine Learning June 5, 2026 By Ankur Garg, Michael Stettler, Aaron Schein, Julius von K\"ugelgen

Discrete Causal Representations from Heterogeneous Domains: A Bayesian Approach with Social Survey Applications

Read the original on arXiv Machine Learning →

arXiv:2606. 06288v1 Announce Type: cross Abstract: Causal representation learning aims to infer the high-level latent causal concepts that give rise to observed low-level measurements.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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