James Robins

Joined

February 2017

Names

James Robins

Emails

****@hsph.harvard.edu (Confirmed)

Personal Links

Career & Education History

Full Professor

Harvard University (harvard.edu)

1982 – 2018

Advisors, Relations & Conflicts

No relations added

Expertise

causal inference

1982 – 2018

Publications

Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
Lin Liu, Rajarshi Mukherjee, James Robins
- 21 Sept 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Deep Learning Methods for Proximal Inference via Maximum Moment Restriction
Benjamin Kompa, David Remy Bellamy, Tom Kolokotrones, James Robins, Andrew Beam
- Published: 31 Oct 2022, Last Modified: 08 Feb 2026
- NeurIPS 2022 Accept
- Readers: Everyone
Estimation of local treatment effects under the binary instrumental variable model
Linbo Wang, Yuexia Zhang, Thomas Richardson, James Robins
- 02 Mar 2022 (modified: 02 Mar 2022)
- OpenReview Archive Direct Upload
- Readers: Everyone
On Modeling and Estimation for the Relative Risk and Risk Difference
Linbo Wang, Thomas Richardson, James Robins
- 18 Sept 2021
- OpenReview Archive Direct Upload
- Readers: Everyone
On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
Lin Liu, Rajarshi Mukherjee, James Robins
- 29 May 2021
- OpenReview Archive Direct Upload
- Readers: Everyone
Efficient estimation of optimal regimes under a no direct effect assumption
Lin Liu, Zach Shahn, James Robins, Andrea Rotnitzky
- 29 May 2021
- OpenReview Archive Direct Upload
- Readers: Everyone
Adaptive estimation of nonparametric functionals
Lin Liu, Rajarshi Mukherjee, James Robins, Eric Tchetgen Tchetgen
- 29 May 2021 (modified: 29 May 2021)
- OpenReview Archive Direct Upload
- Readers: Everyone

James Robins

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators

Deep Learning Methods for Proximal Inference via Maximum Moment Restriction

Estimation of local treatment effects under the binary instrumental variable model

On Modeling and Estimation for the Relative Risk and Risk Difference

On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning

Efficient estimation of optimal regimes under a no direct effect assumption

Adaptive estimation of nonparametric functionals

Co-Authors