no code implementations • 15 Aug 2023 • Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan
Machine learning (ML) methods are proliferating in scientific research.
no code implementations • NeurIPS 2023 • Naoki Egami, Musashi Hinck, Brandon M. Stewart, Hanying Wei
In most scenarios, CSS researchers first obtain labels for documents and then explain labels using interpretable regression analyses in the second step.
1 code implementation • 2 Sep 2021 • Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang
A fundamental goal of scientific research is to learn about causal relationships.
no code implementations • 24 Jul 2020 • Justin Grimmer, Dean Knox, Brandon M. Stewart
We prove under these assumptions, a na\"ive semiparametric regression of $\mathbf{Y}$ on $\mathbf{A}$ is asymptotically unbiased.
no code implementations • 6 Feb 2018 • Naoki Egami, Christian J. Fong, Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart
We argue that nearly all text-based causal inferences depend upon a latent representation of the text and we provide a framework to learn the latent representation.
no code implementations • 30 Oct 2017 • Allison J. B. Chaney, Brandon M. Stewart, Barbara E. Engelhardt
Recommendation systems are ubiquitous and impact many domains; they have the potential to influence product consumption, individuals' perceptions of the world, and life-altering decisions.