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Sensitivity Analysis of Linear Structural Causal Models

ICML 2019 · Probabilistic and scientific modeling › Causal discovery · approach: Causal effect identification · 26 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add bidirected-edge constraints via PushForward to QID (CID vs QID) (ablation)CID · 3-node, both edge typesqueries solved: 68 (21%) -> 320 (100%)Helped
Add PushForward to QID (ablation)CID · 4-node, both edge typesqueries solved: 170,304(29%) -> 555,758(96%)Helped
Add PushForward to QID (ablation)CID · 4-node, bidirected onlyqueries solved: – (0%) -> 50,708(97%)Helped
Add PushForward to QID (ablation)CID · 3-node, bidirected onlyqueries solved: – (0%) -> 109(100%)Helped
Add PushForward to QID, directed-only parameters (ablation)CID · 4-node, directedqueries solved: 14,952(95%) -> 14,952(95%)No clear effect
Topological ordering vs brute-force subset search for pushing bidirected edges (ablation)CID · 3 and 4-node modelsqueries solvedNo clear effect
Replace incomplete QID with complete identification algorithm for directed edges (ablation)CID · 4-node modelsqueries solved: over 99.99% identifiedHelped

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