RieszNet and ForestRiesz: Automatic Debiased Machine Learning with
Neural Nets and Random Forests

v1v2v3 (latest)

RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests

6 October 2021

Victor Chernozhukov

Victor Quintas-Martinez

Vasilis Syrgkanis

ArXiv (abs)PDF HTML

Papers citing "RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests"

11 / 11 papers shown

Title
Stabilized Inverse Probability Weighting via Isotonic Calibration L. Laan Ziming Lin M. Carone Alex Luedtke 84 2 0 10 Nov 2024
Automatic debiasing of neural networks via moment-constrained learning Christian L. Hines Oliver J. Hines CML OOD 158 0 0 29 Sep 2024
General targeted machine learning for modern causal mediation analysis Richard Liu Nicholas T. Williams Kara E. Rudolph Iván Díaz CML 23 3 0 26 Aug 2024
Orthogonal Causal Calibration Justin Whitehouse Christopher Jung Vasilis Syrgkanis Bryan Wilder Zhiwei Steven Wu CML 167 1 0 04 Jun 2024
C-Learner: Constrained Learning for Causal Inference T. Cai Yuri Fonseca Kaiwen Hou Hongseok Namkoong CML 79 1 0 15 May 2024
Addressing Dynamic and Sparse Qualitative Data: A Hilbert Space Embedding of Categorical Variables Anirban Mukherjee Hannah H. Chang CML 45 0 0 22 Aug 2023
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers Parikshit Bansal Amit Sharma CML 84 5 0 26 May 2023
Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions Kazuhiko Shinoda T. Hoshino CML 66 0 0 26 Dec 2022
Inference on Strongly Identified Functionals of Weakly Identified Functions Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 110 17 0 17 Aug 2022
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders S. Jun S. Lee 79 1 0 27 May 2022
Long Story Short: Omitted Variable Bias in Causal Machine Learning Victor Chernozhukov Carlos Cinelli Whitney Newey Amit Sharma Vasilis Syrgkanis CML 66 37 0 26 Dec 2021