1. Machine learning for neutron reflectometry data analysis of two-layer thin films*Notice of Copyright: This manuscript has been authored by UT-Battelle, LLC under Contract DE-AC05-00OR22725 with the U.S. Department of Energy (DOE). The U.S. government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Issue 3 (22nd April 2021) Authors: Doucet, Mathieu; Archibald, Richard K; Heller, William T Journal: Machine learning: science and technology Issue: Volume 2:Issue 3(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Machine learning for neutron scattering at ORNL*. Issue 2 (29th December 2020) Authors: Doucet, Mathieu; Samarakoon, Anjana M; Do, Changwoo; Heller, William T; Archibald, Richard; Alan Tennant, D; Proffen, Thomas; Granroth, Garrett E Journal: Machine learning: science and technology Issue: Volume 2:Issue 2(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗