Work

Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle libraries

Year: 2024

Type: article

Abstract: ss-rVAE classification can generalize from a small labeled data subset with weak orientational disorder to a larger unlabeled dataset with stronger disorder. We apply it to nanoparticle datasets to train a robust classifier and understand physical factors of data variation.

Source: Digital Discovery

DOI: 10.1039/d3dd00196b

Authors: Maxim A. Ziatdinov, Muammer Yusuf Yaman, Yongtao Liu, David Ginger, Sergei V. Kalinin

Institutions: Pacific Northwest National Laboratory, University of Washington, Oak Ridge National Laboratory, Center for Nanophase Materials Sciences, University of Tennessee at Knoxville

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: diamond