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Found 2 papers, 1 papers with code
To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Due to the imbalanced nature of networked observational data, the causal effect predictions for some individuals can severely violate the positivity/overlap assumption, rendering unreliable estimations.
Variational Counterfactual Prediction under Runtime Domain Corruption
We term the co-occurrence of domain shift and inaccessible variables runtime domain corruption, which seriously impairs the generalizability of a trained counterfactual predictor.
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