Scalable Bayesian inference for high-dimensional hierarchical models

We develop a scalable variational method for posterior inference in high-dimensional hierarchical models, with theoretical guarantees and applications to large biomedical datasets. (Example entry — replace with your own paper.)

Recommended citation: Carter, E., Nguyen, A., & Olsson, R. (2025). "Scalable Bayesian inference for high-dimensional hierarchical models." Journal of the American Statistical Association.