We propose an amortized inference strategy for probabilistic programs, one that learns from the past inferences to speed up the future inferences. Our proposed inference strategy is to train neural guidance programs via a minimax game, with the probabilistic program … Continue reading →

Welcome to PPS, workshop on probabilistic programming semantics, on Tuesday, 9 January 2018, colocated right before POPL. This informal workshop aims to bring programming-language and machine-learning researchers together to advance the semantic foundations of probabilistic programming. We are delighted that Erik … Continue reading →