  In this paper, we present Neural Glyph, a system that generates novel glyph
without any training data. The generator and the classifier are trained to
communicate via visual symbols as a medium, which enforces the generator to
come up with a set of distinctive symbols. Our method results in glyphs that
resemble the human-made glyphs, which may imply that the visual appearances of
existing glyphs can be attributed to constraints of communication via writing.
Important tricks that enable this framework are described and the code is made
available.
