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Identifiability Guarantees for Causal Disentanglement from Soft Interventions

NeurIPS 2023 · Probabilistic and scientific modeling › Causal discovery · approach: Causal effect identification · 9 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use CausalDiscrepancyVAE to predict single-gene intervention distributionsCausalDiscrepancyVAE · Perturb-seq single-node interventionsR^2: 0.99 over all genes; 0.95 over most differentially expressed genesHelped
Predict unseen combinations of two interventionsCausalDiscrepancyVAE · Perturb-seq double-node interventionsR^2: 0.98 over all genes; 0.88 over most differentially expressed genesHelped
Predict individual unseen intervention pairsCausalDiscrepancyVAE · Perturb-seq double-node interventionsrecovery of intervention subpopulationsMixed

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