Turning procedural and structural knowledge into programs has established methodologies, but what about turning knowledge into probabilistic models? I explore a few examples of what such a process could look like.
My name is Daniel Holden. I'm a researcher at Ubisoft Montreal using Machine Learning for character animation and other applications. I'm also a Digital Artist and Writer. My interests are Computer Graphics, Game Development, Theory of Computation, and Programming Languages.