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stat.ML2021★ 2 cited
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies
Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel
Estimating individualized treatment effects (ITEs) from observational data is crucial for decision-making. In order to obtain unbiased ITE estimates, a common assumption is that al…
stat.ML2021★ 1 cited
Generalizing Off-Policy Learning under Sample Selection Bias
Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel
Learning personalized decision policies that generalize to the target population is of great relevance. Since training data is often not representative of the target population, st…