322 citations · 322 across the 13 of their papers we have counts for
5 papers · 1 filter
OrthoGen: A Generative Orthogonal Learner for Time-Varying Treatments
Tomàs Garriga, Valentyn Melnychuk, Konstantin Hess +4
Estimating conditional distributional potential outcomes (CDPOs) over time is important in medicine (e.g., to estimate patient-specific risks under different treatment sequences).…
Representation Learning for Exact Preimages
Konstantin Hess, Stefan Feuerriegel
Modern neural predictors can model highly nonlinear maps, but many scientific and engineering tasks require reasoning in the opposite direction: given a performance or safety level…
Causal methods for LLM development and evaluation
Dennis Frauen, Marie Brockschmidt, Konstantin Hess +10
Large language model (LLM) development is currently driven by large-scale empirical iteration over data mixtures, reward models, routing strategies, and evaluation pipelines. Here,…
Debiased neural operators for estimating functionals
Konstantin Hess, Dennis Frauen, Niki Kilbertus +1
Neural operators are widely used to approximate solution maps of complex physical systems. In many applications, however, the goal is not to recover the full solution trajectory, b…
Targeted Synthetic Control Method
Yuxin Wang, Dennis Frauen, Emil Javurek +3
The synthetic control method (SCM) estimates causal effects in panel data with a single-treated unit by constructing a counterfactual outcome as a weighted combination of untreated…