Abstract
Presented are results of two numerical experiments: the whole chloroplast genome chaos game representation of
Cannabis sativa and the comparison of two state-of-the-art neural network architectures applied to the neural style
transfer problem. A brief explanation of the chaos game representation is given followed by results illustrating that the
whole chloroplast genome has global structure. An explication of neural style transfer and the ResNet and FractalNet
neural network architectures is then given followed by results when both networks are trained to learn the underlying
feature representation of an image of Cannabis sativa. Finally, the artistic motivation of these numerical experiments
is presented in the context of the genotype-phenotype distinction.
