39 citations · 107 across the 30 of their papers we have counts for
4 papers · 1 filter
Black-Box Policy Search with Probabilistic Programs
Jan-Willem van de Meent, Brooks Paige, David Tolpin +1
In this work, we explore how probabilistic programs can be used to represent policies in sequential decision problems. In this formulation, a probabilistic program is a black-box s…
Maximum a Posteriori Estimation by Search in Probabilistic Programs
David Tolpin, Frank Wood
We introduce an approximate search algorithm for fast maximum a posteriori probability estimation in probabilistic programs, which we call Bayesian ascent Monte Carlo (BaMC). Proba…
Path Finding under Uncertainty through Probabilistic Inference
David Tolpin, Brooks Paige, Jan Willem van de Meent +1
We introduce a new approach to solving path-finding problems under uncertainty by representing them as probabilistic models and applying domain-independent inference algorithms to…
Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs
David Tolpin, Jan Willem van de Meent, Brooks Paige +1
We introduce an adaptive output-sensitive Metropolis-Hastings algorithm for probabilistic models expressed as programs, Adaptive Lightweight Metropolis-Hastings (AdLMH). The algori…