no code implementations • 2 Sep 2020 • Sergei V. Kalinin, Shuai Zhang, Mani Valleti, Harley Pyles, David Baker, James J. De Yoreo, Maxim Ziatdinov
The dynamic of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally invariant variational autoencoder-based analysis of orientation and shape evolution.
Soft Condensed Matter
