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Coarsening Linear Non-Gaussian Causal Models with Cycles
Linear non-Gaussian cyclic models yield recoverable low-dimensional acyclic summaries representing observational equivalence classes, learnable in cubic time with sample complexity bounds.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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AI panel: 12 of 20 reviewers recommend it
lenient 2/5
medium 7/10
strict 3/5