  Shallow Art presents, implements, and tests the use of simple single-output
classification and regression models for the purpose of art generation. Various
machine learning algorithms are trained on collections of computer generated
images, artworks from Vincent van Gogh, and artworks from Rembrandt van Rijn.
These models are then provided half of an image and asked to complete the
missing side. The resulting images are displayed, and we explore implications
for computational creativity.
