Inference on weighted average value function in high-dimensional state space. - Victor Chernozhukov; Whitney Newey; Vira Semenova (CoRR, 2019)

Adversarial Estimation of Riesz Representers. - Victor Chernozhukov; Whitney Newey; Rahul Singh; Vasilis Syrgkanis (CoRR, 2021)

A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees. - Victor Chernozhukov; Whitney K. Newey; Rahul Singh (CoRR, 2021)

Omitted Variable Bias in Machine Learned Causal Models. - Victor Chernozhukov; Carlos Cinelli; Whitney Newey; Amit Sharma 007; Vasilis Syrgkanis (CoRR, 2021)

RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests. - Victor Chernozhukov; Whitney Newey; Victor Quintas-Martinez; Vasilis Syrgkanis (ICML, 2022)

Inference on Strongly Identified Functionals of Weakly Identified Functions. - Andrew Bennett; Nathan Kallus; Xiaojie Mao; Whitney Newey; Vasilis Syrgkanis; Masatoshi Uehara (COLT, 2023)

Minimax Instrumental Variable Regression and L2 Convergence Guarantees without Identification or Closedness. - Andrew Bennett; Nathan Kallus; Xiaojie Mao; Whitney Newey; Vasilis Syrgkanis; Masatoshi Uehara (COLT, 2023)

Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness. - Andrew Bennett; Nathan Kallus; Xiaojie Mao; Whitney Newey; Vasilis Syrgkanis; Masatoshi Uehara (CoRR, 2023)

Source Condition Double Robust Inference on Functionals of Inverse Problems. - Andrew Bennett; Nathan Kallus; Xiaojie Mao; Whitney Newey; Vasilis Syrgkanis; Masatoshi Uehara (CoRR, 2023)