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Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
Observable Neural ODEs link control-theoretic observability to causal identifiability in continuous-time settings with hidden confounders and outperform recent sequence models in forecasting under alternative treatments.
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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AI panel: 11 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 1/5