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Found 4 papers, 4 papers with code
Causal Machine Learning for Cost-Effective Allocation of Development Aid
Then, we demonstrate our framework using real-world HIV data.
Addressing distributional shifts in operations management: The case of order fulfillment in customized production
We empirically validate our proposed approach using real-world data from a job shop production that supplies large metal components to an oil platform construction yard.
Estimating Conditional Average Treatment Effects with Missing Treatment Information
Although this is a widespread problem in practice, CATE estimation with missing treatments has received little attention.
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies
To this end, we develop the Deconfounding Temporal Autoencoder, a novel method that leverages observed noisy proxies to learn a hidden embedding that reflects the true hidden confounders.
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