  Random electron systems show rich phases such as Anderson insulator,
diffusive metal, quantum and anomalous quantum Hall insulator, Weyl semimetal,
as well as strong/weak topological insulators. Eigenfunctions of each matter
phase have specific features, but due to the random nature of systems, judging
the matter phase from eigenfunctions is difficult. Here we propose the deep
learning algorithm to capture the features of eigenfunctions.
Localization-delocalization transition as well as disordered Chern
insulator-Anderson insulator transition is discussed.
