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cs.LG2026
AutoCause: A Python framework that automates expert decisions in environmental time-series causal discovery
Marco Ruiz, Miguel Arana-Catania, David R. Ardila +1
Environmental time-series causal discovery requires expert decisions about method choice, conditional-independence tests, lag horizons, sample-size adequacy, multiple-testing contr…
cs.LG2026
Causal-Audit: A Framework for Risk Assessment of Assumption Violations in Time-Series Causal Discovery
Marco Ruiz, Miguel Arana-Catania, David R. Ardila +1
Time-series causal discovery methods rely on assumptions such as stationarity, regular sampling, and bounded temporal dependence. When these assumptions are violated, structure lea…