Victor Chernozhukov

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 31

Top Topics

Quantile Regression

Top Venues

J. Mach. Learn. Res.

Publications

Philipp Bach, Malte S. Kurz, Victor Chernozhukov, Martin Spindler, Sven Klaassen
. J. Stat. Softw. 108 (3) (2024)
Sven Klaassen, Jan Teichert-Kluge, Philipp Bach, Victor Chernozhukov, Martin Spindler, Suhas Vijaykumar
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data. CoRR (2024)
Victor Chernozhukov, Christian Hansen, Nathan Kallus, Martin Spindler, Vasilis Syrgkanis
Applied Causal Inference Powered by ML and AI. CoRR (2024)
Philipp Bach, Oliver Schacht, Victor Chernozhukov, Sven Klaassen, Martin Spindler
Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study. CLeaR (2024)
Patrick Bajari, Zhihao Cen, Victor Chernozhukov, Manoj Manukonda, Suhas Vijaykumar, Jin Wang, Ramón Huerta, Junbo Li, Ling Leng, George Monokroussos, Shan Wan
Hedonic Prices and Quality Adjusted Price Indices Powered by AI. CoRR (2023)
Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. NeurIPS (2023)
Victor Chernozhukov, Whitney Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. ICML (2022)
Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler
DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python. J. Mach. Learn. Res. 23 (2022)
Masatoshi Uehara, Haruka Kiyohara, Andrew Bennett, Victor Chernozhukov, Nan Jiang, Nathan Kallus, Chengchun Shi, Wen Sun
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs. CoRR (2022)
Gianluca Detommaso, Michael Brückner, Philip Schulz, Victor Chernozhukov
Causal Bias Quantification for Continuous Treatment. CoRR (2021)
Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis
Omitted Variable Bias in Machine Learned Causal Models. CoRR (2021)
Victor Chernozhukov, Whitney K. Newey, Rahul Singh
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees. CoRR (2021)
Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler
DoubleML - An Object-Oriented Implementation of Double Machine Learning in R. CoRR (2021)
Xi Chen, Victor Chernozhukov, Iván Fernández-Val, Scott Kostyshak, Ye Luo
Shape-Enforcing Operators for Generic Point and Interval Estimators of Functions. J. Mach. Learn. Res. 22 (2021)
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Deeply-Debiased Off-Policy Interval Estimation. CoRR (2021)
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Deeply-Debiased Off-Policy Interval Estimation. ICML (2021)
Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler
DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python. CoRR (2021)
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. CoRR (2021)
Victor Chernozhukov, Whitney Newey, Rahul Singh, Vasilis Syrgkanis
Adversarial Estimation of Riesz Representers. CoRR (2021)
Shuowen Chen, Victor Chernozhukov, Iván Fernández-Val, Ye Luo
SortedEffects: Sorted Causal Effects in R. R J. 12 (1) (2020)
Xi Chen, Victor Chernozhukov, Ye Luo, Martin Spindler
Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data. CoRR (2019)
Victor Chernozhukov, Whitney Newey, Vira Semenova
Inference on weighted average value function in high-dimensional state space. CoRR (2019)
Victor Chernozhukov, Mert Demirer, Greg Lewis, Vasilis Syrgkanis
Semi-Parametric Efficient Policy Learning with Continuous Actions. NeurIPS (2019)
Mert Demirer, Vasilis Syrgkanis, Greg Lewis, Victor Chernozhukov
Semi-Parametric Efficient Policy Learning with Continuous Actions. CoRR (2019)
Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis
Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models. CoRR (2018)
Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu
Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data. CoRR (2018)
Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu
Exact and Robust Conformal Inference Methods for Predictive Machine Learning with Dependent Data. COLT (2018)
Guillaume Carlier, Victor Chernozhukov, Alfred Galichon
Vector quantile regression beyond the specified case. J. Multivar. Anal. 161 (2017)
Mingli Chen, Victor Chernozhukov, Iván Fernández-Val, Blaise Melly
Counterfactual: An R Package for Counterfactual Analysis. R J. 9 (1) (2017)
Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, Iván Fernández-Val
quantreg.nonpar: An R Package for Performing Nonparametric Series Quantile Regression. R J. 8 (2) (2016)
Victor Chernozhukov, Chris Hansen, Martin Spindler
hdm: High-Dimensional Metrics. R J. 8 (2) (2016)
Victor Chernozhukov, Christian Hansen, Yuan Liao
A lava attack on the recovery of sums of dense and sparse signals. CoRR (2015)