Drawing on process philosophy, Munster approaches computational experience through its relations and operations. She combines deep learning?the subfield of machine learning that uses neural network architectures?and aesthetics to offer a way to understand the insensible and frequently imperceptible forms of nonlinear and continuously modulating statistical function.