Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals. - AmirEmad Ghassami; Andrew Ying; Ilya Shpitser; Eric Tchetgen Tchetgen (CoRR, 2021)

Adaptive estimation of nonparametric functionals. - Lin Liu; Rajarshi Mukherjee; James M. Robins; Eric Tchetgen Tchetgen (J. Mach. Learn. Res., 2021)

Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference. - AmirEmad Ghassami; Andrew Ying; Ilya Shpitser; Eric Tchetgen Tchetgen (AISTATS, 2022)

End-to-End Balancing for Causal Continuous Treatment-Effect Estimation. - Mohammad Taha Bahadori; Eric Tchetgen Tchetgen; David Heckerman (ICML, 2022)

Validating Causal Inference Methods. - Harsh Parikh; Carlos Varjao; Louise Xu; Eric Tchetgen Tchetgen (ICML, 2022)

Evaluating Causal Inference Methods. - Harsh Parikh; Carlos Varjao; Louise Xu; Eric Tchetgen Tchetgen (CoRR, 2022)

Selective Machine Learning of the Average Treatment Effect with an Invalid Instrumental Variable. - Baoluo Sun; Yifan Cui; Eric Tchetgen Tchetgen (J. Mach. Learn. Res., 2022)

The Proximal ID Algorithm. - Ilya Shpitser; Zach Wood-Doughty; Eric J. Tchetgen Tchetgen (J. Mach. Learn. Res., 2023)

Proximal Causal Inference for Synthetic Control with Surrogates. - Jizhou Liu; Eric Tchetgen Tchetgen; Carlos Varjão (AISTATS, 2024)