Interview, Building Trust in Medical AI Algorithms with Veridical Data Science

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

(2022) Nate Breznau et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Veridical data science

(2020) Bin Yu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Stable Discovery of Interpretable Subgroups via Calibration in Causal Studies

(2020) Raaz Dwivedi et al.   INTERNATIONAL STATISTICAL REVIEW

Metalearners for estimating heterogeneous treatment effects using machine learning

(2019) Sören R. Künzel et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Iterative random forests to discover predictive and stable high-order interactions

(2018) Sumanta Basu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Artificial intelligence and statistics

(2018) Bin Yu et al.   Frontiers of Information Technology & Electronic Engineering

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

(2016) Siqi Wu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Stability

(2013) Bin Yu   BERNOULLI