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cs.LG2023★ 1 cited
The Challenges of Hyperparameter Tuning for Accurate Causal Effect Estimation
Damian Machlanski, Spyridon Samothrakis, Paul Clarke
ML is playing an increasingly crucial role in estimating causal effects of treatments on outcomes from observational data. Many ML methods (`causal estimators') have been proposed…
cs.LG2022
Undersmoothing Causal Estimators with Generative Trees
Damian Machlanski, Spyros Samothrakis, Paul Clarke
Inferring individualised treatment effects from observational data can unlock the potential for targeted interventions. It is, however, hard to infer these effects from observation…