  Three-dimensional random electron systems undergo quantum phase transitions
and show rich phase diagrams. Examples of the phases are the band gap
insulator, Anderson insulator, strong and weak topological insulators, Weyl
semimetal, and diffusive metal. As in the previous paper on two-dimensional
quantum phase transitions [J. Phys. Soc. Jpn. vol. 85, 123706 (2016)], we use
an image recognition algorithm based on a multilayered convolutional neural
network to identify which phase the eigenfunction belongs to. The Anderson
model for localization-delocalization transition, the Wilson--Dirac model for
topological insulators, and the layered Chern insulator model for Weyl
semimetal are studied. The situation where the standard transfer matrix
approach is not applicable is also treated by this method.
