Double/Debiased/Neyman Machine Learning of Treatment Effects

30 January 2017

Papers citing "Double/Debiased/Neyman Machine Learning of Treatment Effects"

40 / 40 papers shown

Title
Semiparametric Counterfactual Regression Kwangho Kim OffRL 39 0 0 03 Apr 2025
Detecting clinician implicit biases in diagnoses using proximal causal inference Kara Liu Russ Altman Vasilis Syrgkanis CML 48 0 0 27 Jan 2025
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation Jikai Jin Vasilis Syrgkanis CML 67 1 0 22 Feb 2024
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 32 9 0 19 Nov 2023
Nonparametric estimation of a covariate-adjusted counterfactual treatment regimen response curve Ashkan Ertefaie Luke Duttweiler Brent A. Johnson Mark van der Laan 13 0 0 28 Sep 2023
Addressing Dynamic and Sparse Qualitative Data: A Hilbert Space Embedding of Categorical Variables Anirban Mukherjee Hannah H. Chang CML 21 0 0 22 Aug 2023
Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning Byung-Kwan Lee Junho Kim Yonghyun Ro AAML 18 9 0 14 Jul 2023
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations Hammaad Adam Fan Yin Huibin Mary Hu Neil A. Tenenholtz Lorin Crawford Lester W. Mackey Allison Koenecke 22 1 0 20 Jun 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning K. Kim J. Zubizarreta 26 6 0 06 Jun 2023
Estimation Beyond Data Reweighting: Kernel Method of Moments Heiner Kremer Yassine Nemmour Bernhard Schölkopf Jia-Jie Zhu 36 7 0 18 May 2023
Doubly Robust Counterfactual Classification K. Kim Edward H. Kennedy J. Zubizarreta OffRL 33 5 0 15 Jan 2023
Debiased machine learning for estimating the causal effect of urban traffic on pedestrian crossing behaviour K. Kamal Bilal Farooq 38 3 0 21 Dec 2022
On LASSO for High Dimensional Predictive Regression Ziwei Mei Zhentao Shi 18 9 0 14 Dec 2022
Neighborhood Adaptive Estimators for Causal Inference under Network Interference A. Belloni Fei Fang A. Volfovsky CML 43 6 0 07 Dec 2022
Meta-analysis of individualized treatment rules via sign-coherency Jay Jojo Cheng J. Huling Guanhua Chen 26 0 0 28 Nov 2022
Fair Effect Attribution in Parallel Online Experiments Alexander K. Buchholz Vito Bellini Giuseppe Di Benedetto Yannik Stein M. Ruffini Fabian Moerchen 23 1 0 15 Oct 2022
Finite- and Large- Sample Inference for Model and Coefficients in High-dimensional Linear Regression with Repro Samples P. Wang Min-ge Xie Linjun Zhang 40 5 0 19 Sep 2022
Inference on Strongly Identified Functionals of Weakly Identified Functions Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 32 15 0 17 Aug 2022
A Causal Research Pipeline and Tutorial for Psychologists and Social Scientists M. Vowels CML 32 2 0 10 Jun 2022
Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-offs: A Causal Inference Approach Xiaohui Liu Sean Qian Hock-Hai Teo Weichao Ma 34 10 0 05 Jun 2022
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage Alexis Bellot Anish Dhir G. Prando CML 18 11 0 29 May 2022
Measuring the Impact of Taxes and Public Services on Property Values: A Double Machine Learning Approach Isaiah Hull Anna Grodecka-Messi 11 2 0 23 Mar 2022
Statistical Learning for Individualized Asset Allocation Yi Ding Yingying Li Rui Song 25 0 0 20 Jan 2022
A framework for causal segmentation analysis with machine learning in large-scale digital experiments N. Hejazi Wenjing Zheng Sathyanarayan Anand CML 12 2 0 01 Nov 2021
Text as Causal Mediators: Research Design for Causal Estimates of Differential Treatment of Social Groups via Language Aspects Katherine A. Keith Douglas Rice Brendan O'Connor CML 19 3 0 15 Sep 2021
DoWhy: Addressing Challenges in Expressing and Validating Causal Assumptions Amit Sharma Vasilis Syrgkanis Cheng Zhang Emre Kıcıman 18 26 0 27 Aug 2021
Federated Causal Inference in Heterogeneous Observational Data Ruoxuan Xiong Allison Koenecke Michael A. Powell Zhu Shen Joshua T. Vogelstein Susan Athey FedML CML 23 45 0 25 Jul 2021
Demystifying statistical learning based on efficient influence functions Oliver Hines O. Dukes Karla Diaz-Ordaz S. Vansteelandt TDI 19 110 0 01 Jul 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 17 68 0 14 Mar 2021
Inference for natural mediation effects under case-cohort sampling with applications in identifying COVID-19 vaccine correlates of protection David Benkeser Iván Díaz J. Ran 16 9 0 03 Mar 2021
Machine Learning Advances for Time Series Forecasting Ricardo P. Masini M. C. Medeiros Eduardo F. Mendes AI4TS 21 270 0 23 Dec 2020
Semiparametric proximal causal inference Yifan Cui Hongming Pu Xu Shi Wang Miao E. T. Tchetgen Tchetgen 23 100 0 17 Nov 2020
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions Yanbo Xu Divyat Mahajan Liz Manrao Amit Sharma Emre Kıcıman CML 10 2 0 11 Nov 2020
DoWhy: An End-to-End Library for Causal Inference Amit Sharma Emre Kıcıman CML 12 157 0 09 Nov 2020
Dynamic Causal Effects Evaluation in A/B Testing with a Reinforcement Learning Framework C. Shi Xiaoyu Wang S. Luo Hongtu Zhu Jieping Ye R. Song CML OffRL 27 33 0 05 Feb 2020
Machine learning in policy evaluation: new tools for causal inference N. Kreif K. DiazOrdaz ELM CML 25 45 0 01 Mar 2019
Using Embeddings to Correct for Unobserved Confounding in Networks Victor Veitch Yixin Wang David M. Blei CML 15 56 0 11 Feb 2019
Automatic Debiased Machine Learning of Causal and Structural Effects Victor Chernozhukov Whitney Newey Rahul Singh CML AI4CE 24 103 0 14 Sep 2018
Significance testing in non-sparse high-dimensional linear models Yinchu Zhu Jelena Bradic 37 31 0 07 Oct 2016
Locally Robust Semiparametric Estimation Victor Chernozhukov J. Escanciano Hidehiko Ichimura Whitney Newey J. M. Robins 27 205 0 29 Jul 2016