A Double Machine Learning Trend Model for Citizen Science Data

27 October 2022

Papers citing "A Double Machine Learning Trend Model for Citizen Science Data"

8 / 8 papers shown

Title
Towards optimal doubly robust estimation of heterogeneous causal effects Edward H. Kennedy CML 38 314 0 29 Apr 2020
CausalML: Python Package for Causal Machine Learning Huigang Chen Totte Harinen Jeong-Yoon Lee Mike Yung Zhenyu Zhao CML 6 111 0 25 Feb 2020
Quasi-Oracle Estimation of Heterogeneous Treatment Effects Xinkun Nie Stefan Wager CML 22 640 0 13 Dec 2017
Some methods for heterogeneous treatment effect estimation in high-dimensions Scott Powers Junyang Qian Kenneth Jung Alejandro Schuler N. Shah Trevor Hastie Robert Tibshirani CML 33 218 0 01 Jul 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning Sören R. Künzel Jasjeet Sekhon Peter J. Bickel Bin Yu CML 32 908 0 12 Jun 2017
Generalized Random Forests Susan Athey J. Tibshirani Stefan Wager 45 1,343 0 05 Oct 2016
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests Stefan Wager Susan Athey SyDa CML 49 2,463 0 14 Oct 2015
Supplementary Appendix for "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls" A. Belloni Victor Chernozhukov Christian B. Hansen 98 1,399 0 27 May 2013