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2020 – today
- 2025
[i20]Philipp Bach, Victor Chernozhukov, Sven Klaassen, Martin Spindler, Jan Teichert-Kluge, Suhas Vijaykumar:
Adventures in Demand Analysis Using AI. CoRR abs/2501.00382 (2025)- 2024
- [j8]Philipp Bach, Malte S. Kurz, Victor Chernozhukov, Martin Spindler, Sven Klaassen:
DoubleML: An Object-Oriented Implementation of Double Machine Learning in R. J. Stat. Softw. 108(3) (2024) - [c6]Philipp Bach, Oliver Schacht, Victor Chernozhukov, Sven Klaassen, Martin Spindler:
Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study. CLeaR 2024: 1065-1117 - [i19]Sven Klaassen, Jan Teichert-Kluge, Philipp Bach, Victor Chernozhukov, Martin Spindler, Suhas Vijaykumar:
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data. CoRR abs/2402.01785 (2024) - [i18]Victor Chernozhukov, Christian Hansen, Nathan Kallus, Martin Spindler, Vasilis Syrgkanis:
Applied Causal Inference Powered by ML and AI. CoRR abs/2403.02467 (2024) - [i17]Zhaomeng Chen, Junting Duan, Victor Chernozhukov, Vasilis Syrgkanis:
Automatic Doubly Robust Forests. CoRR abs/2412.07184 (2024) - 2023
- [c5]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 - [i16]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 abs/2305.00044 (2023) - 2022
- [j7]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: 53:1-53:6 (2022) - [c4]Victor Chernozhukov, Whitney Newey, Victor Quintas-Martinez, Vasilis Syrgkanis:
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. ICML 2022: 3901-3914 - [i15]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 abs/2207.13081 (2022) - 2021
- [j6]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: 220:1-220:42 (2021) - [c3]Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song:
Deeply-Debiased Off-Policy Interval Estimation. ICML 2021: 9580-9591 - [i14]Victor Chernozhukov, Whitney Newey, Rahul Singh, Vasilis Syrgkanis:
Adversarial Estimation of Riesz Representers. CoRR abs/2101.00009 (2021) - [i13]Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler:
DoubleML - An Object-Oriented Implementation of Double Machine Learning in R. CoRR abs/2103.09603 (2021) - [i12]Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler:
DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python. CoRR abs/2104.03220 (2021) - [i11]Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song:
Deeply-Debiased Off-Policy Interval Estimation. CoRR abs/2105.04646 (2021) - [i10]Victor Chernozhukov, Whitney K. Newey, Rahul Singh:
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees. CoRR abs/2105.15197 (2021) - [i9]Gianluca Detommaso, Michael Brückner, Philip Schulz, Victor Chernozhukov:
Causal Bias Quantification for Continuous Treatment. CoRR abs/2106.09762 (2021) - [i8]Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis:
RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. CoRR abs/2110.03031 (2021) - [i7]Victor Chernozhukov, Carlos Cinelli, Whitney Newey, Amit Sharma, Vasilis Syrgkanis:
Omitted Variable Bias in Machine Learned Causal Models. CoRR abs/2112.13398 (2021) - 2020
- [j5]Shuowen Chen, Victor Chernozhukov, Iván Fernández-Val, Ye Luo:
SortedEffects: Sorted Causal Effects in R. R J. 12(1): 131 (2020)
2010 – 2019
- 2019
- [c2]Victor Chernozhukov, Mert Demirer, Greg Lewis, Vasilis Syrgkanis:
Semi-Parametric Efficient Policy Learning with Continuous Actions. NeurIPS 2019: 15039-15049 - [i6]Mert Demirer, Vasilis Syrgkanis, Greg Lewis, Victor Chernozhukov:
Semi-Parametric Efficient Policy Learning with Continuous Actions. CoRR abs/1905.10116 (2019) - [i5]Victor Chernozhukov, Whitney Newey, Vira Semenova:
Inference on weighted average value function in high-dimensional state space. CoRR abs/1908.09173 (2019) - [i4]Xi Chen, Victor Chernozhukov, Ye Luo, Martin Spindler:
Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data. CoRR abs/1912.12867 (2019) - 2018
- [c1]Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu:
Exact and Robust Conformal Inference Methods for Predictive Machine Learning with Dependent Data. COLT 2018: 732-749 - [i3]Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu:
Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data. CoRR abs/1802.06300 (2018) - [i2]Victor Chernozhukov, Denis Nekipelov, Vira Semenova, Vasilis Syrgkanis:
Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models. CoRR abs/1806.04823 (2018) - 2017
- [j4]Guillaume Carlier, Victor Chernozhukov, Alfred Galichon:
Vector quantile regression beyond the specified case. J. Multivar. Anal. 161: 96-102 (2017) - [j3]Mingli Chen, Victor Chernozhukov, Iván Fernández-Val, Blaise Melly:
Counterfactual: An R Package for Counterfactual Analysis. R J. 9(1): 370 (2017) - 2016
- [j2]Victor Chernozhukov, Chris Hansen, Martin Spindler:
hdm: High-Dimensional Metrics. R J. 8(2): 185 (2016) - [j1]Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, Iván Fernández-Val:
quantreg.nonpar: An R Package for Performing Nonparametric Series Quantile Regression. R J. 8(2): 370 (2016) - 2015
- [i1]Victor Chernozhukov, Christian Hansen, Yuan Liao:
A lava attack on the recovery of sums of dense and sparse signals. CoRR abs/1502.03155 (2015)
Coauthor Index
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