4 citations · 4 across the 1 of their papers we have counts for
3 papers
stat.ML2022★ 4 cited
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects
Tobias Hatt, Jeroen Berrevoets, Alicia Curth +2
Estimating heterogeneous treatment effects is an important problem across many domains. In order to accurately estimate such treatment effects, one typically relies on data from ob…
cs.LG2021
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units
Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt +1
Clinical practice in intensive care units (ICUs) requires early warnings when a patient's condition is about to deteriorate so that preventive measures can be undertaken. To this e…
cs.LG2021
Estimating Average Treatment Effects via Orthogonal Regularization
Tobias Hatt, Stefan Feuerriegel
Decision-making often requires accurate estimation of treatment effects from observational data. This is challenging as outcomes of alternative decisions are not observed and have…