Deconfounding Scores and Representation Learning for Causal Effect Estimation with Weak Overlap

Deconfounding Scores and Representation Learning for Causal Effect Estimation with Weak Overlap explores A theoretical framework for causal effect estimation that improves overlap conditions using novel 'deconfounding scores' for high-dimensional data.. Commercial viability score: 3/10 in Causal Inference.