From the 1 of 12 linked papers with an AI index.
4 papers · 1 filter
Verifying formulas for interventional distributions
Francesco Freni, Leonard Henckel, Sebastian Weichwald
The paper defines the verification problem for causal graphical models—checking whether a specific observational formula correctly identifies a target interventional distribution—a…
A Topological Sorting Criterion for Random Causal Directed Acyclic Graphs
Alexander G. Reisach, Antoine Chambaz, Gilles Blanchard +1
Random directed acyclic graphs (DAGs) based on imposing an order on ErdÅs-Rényi and scale free random graphs are widely used for evaluating causal discovery algorithms. We show t…
The Case for Time in Causal DAGs
Alexander G. Reisach, Alberto Suárez, Sebastian Weichwald +1
We make the case for incorporating a notion of time into causal directed acyclic graphs (DAGs). We demonstrate that nontemporal causal DAGs are ambiguous and obstruct justification…
Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the Past
Nikolaj Thams, Rikke Søndergaard, Sebastian Weichwald +1
Instrumental variable (IV) regression relies on instruments to infer causal effects from observational data with unobserved confounding. We consider IV regression in time series mo…