1.1k citations · 1.1k across the 4 of their papers we have counts for
6 papers
Linear Aggregation in Tree-based Estimators
Sören R. Künzel, Theo F. Saarinen, Edward W. Liu +1
Regression trees and their ensemble methods are popular methods for nonparametric regression: they combine strong predictive performance with interpretable estimators. To improve t…
Causaltoolbox---Estimator Stability for Heterogeneous Treatment Effects
Sören R. Künzel, Simon J. S. Walter, Jasjeet S. Sekhon
Estimating heterogeneous treatment effects has become increasingly important in many fields and life and death decisions are now based on these estimates: for example, selecting a…
Transfer Learning for Estimating Causal Effects using Neural Networks
Sören R. Künzel, Bradly C. Stadie, Nikita Vemuri +3
We develop new algorithms for estimating heterogeneous treatment effects, combining recent developments in transfer learning for neural networks with insights from the causal infer…
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning
Sören R. Künzel, Jasjeet S. Sekhon, Peter J. Bickel +1
There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of meta-algorithms that can ta…
A Comprehensive Statistical Description of Radio-Through--Ray Spectral Energy Distributions of All Known Blazars
Peiyuan Mao, C. Megan Urry, Francesco Massaro +3
We combined multi-wavelength data for blazars from the Roma-BZCAT catalog and analyzed hundreds of X-ray spectra. We present the fluxes and Spectral Energy Distributions (SEDs), in…
Remarks on Kneip's linear smoothers
Sören R. Künzel, David Pollard, Dana Yang
We were trying to understand the analysis provided by Kneip (1994, Ordered Linear Smoothers). In particular we wanted to persuade ourselves that his results imply the oracle inequa…