5 citations · 7 across the 5 of their papers we have counts for
5 papers
Nonparametric Regression for Random Unbiased Perturbations
Anna Lyubarskaja, Dominik Rothenhäusler
We study nonparametric regression with covariates and outcome under random unbiased perturbations (RUPs) of the conditional distribution , where the marginal distribut…
Which Covariates to Adjust for? Specification-robust Causal Inference in Observational Studies
Aditya Ghosh, Dominik Rothenhäusler
In observational causal inference, domain knowledge often leaves multiple covariate adjustments plausible, yet which of them satisfy ignorability is not testable. Different adjustm…
Predicting data value before collection: A coefficient for prioritizing sources under random distribution shift
Ivy Zhang, Dominik Rothenhäusler
Researchers often face choices between multiple data sources that differ in quality, cost, and representativeness. Which sources will most improve predictive performance? We study…
Model selection for estimation of causal parameters
Dominik Rothenhäusler
A popular technique for selecting and tuning machine learning estimators is cross-validation. Cross-validation evaluates overall model fit, usually in terms of predictive accuracy.…
Incremental causal effects
Dominik Rothenhäusler, Bin Yu
Causal evidence is needed to act and it is often enough for the evidence to point towards a direction of the effect of an action. For example, policymakers might be interested in e…