Research map / Probabilistic and scientific modeling / Causal discovery
Causal Effect Identifiability under Partial-Observability
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use embedding factors and minimum viable embedding factors (MVEFs) to identify gc-factors under partial observability, combined via exact cover (GID-PO algorithm) | causal effect identification under partial observability (GID-PO) · theoretical; Fig. 1/Fig. 7 example graph | identifiability of Px(y) | Helped |
| Naive gc-factor identification using only full-graph factors F (no projection onto V') versus gc-decomposition on projected graph (ablation) | Px(y) in Fig. 7a graph · theoretical example | identifiability of Px(y) | Hurt |
| Run GID-PO's MVEF-based identification versus naive exhaustive check of Lemma 3 (O(mn^4 2^n)) | GID-PO algorithm complexity · theoretical complexity analysis | runtime complexity | Helped |
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