This week’s ACM Tech News has featured our recent work on Transfer Learning for Bayesian Error Estimation (TL-BEE):

https://technews.acm.org/archives.cfm?fo=2022-03-mar/mar-11-2022.html

This study has also received spotlight on the Department of Energy (DOE), Office of Science website:

https://www.energy.gov/science/office-science

The work has been recently published in Cell Press Patterns, and the full article can be accessed at the link below:

Omar Maddouri, Xiaoning Qian, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon, “Robust Importance Sampling for Error Estimation in the Context of Optimal Bayesian Transfer Learning,” Patterns, 2022, DOI: https://doi.org/10.1016/j.patter.2021.100428