Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives

Jonathan Warrell, Mark Gerstein

Deep Probabilistic Programming (DPP) allows powerful models based on recursive computation to be learned using efficient deep-learning optimization techniques. Additionally, DPP of…