29 citations · 32 across the 4 of their papers we have counts for
4 papers
Augmented Inverse Hybrid Weighting: Robust Inference under Deterministic and Random Distribution Shifts
Ying Jin, Dominik Rothenhäusler
Reweighting source samples to match a target covariate distribution is a standard response to distribution shift when generalizing evidence from one population to another. This str…
Beyond Reweighting: On the Predictive Role of Covariate Shift in Effect Generalization
Ying Jin, Naoki Egami, Dominik Rothenhäusler
Many existing approaches to generalizing statistical inference amidst distribution shift operate under the covariate shift assumption, which posits that the conditional distributio…
Causal aggregation: estimation and inference of causal effects by constraint-based data fusion
Jaime Roquero Gimenez, Dominik Rothenhäusler
In causal inference, it is common to estimate the causal effect of a single treatment variable on an outcome. However, practitioners may also be interested in the effect of simulta…
backShift: Learning causal cyclic graphs from unknown shift interventions
Dominik Rothenhäusler, Christina Heinze, Jonas Peters +1
We propose a simple method to learn linear causal cyclic models in the presence of latent variables. The method relies on equilibrium data of the model recorded under a specific ki…