15 citations · 30 across the 5 of their papers we have counts for
5 papers
Pearl: A Production-ready Reinforcement Learning Agent
Zheqing Zhu, Rodrigo de Salvo Braz, Jalaj Bhandari +12
Reinforcement learning (RL) is a versatile framework for optimizing long-term goals. Although many real-world problems can be formalized with RL, learning and deploying a performan…
Exact Inference for Relational Graphical Models with Interpreted Functions: Lifted Probabilistic Inference Modulo Theories
Rodrigo de Salvo Braz, Ciaran O'Reilly
Probabilistic Inference Modulo Theories (PIMT) is a recent framework that expands exact inference on graphical models to use richer languages that include arithmetic, equalities, a…
Anytime Exact Belief Propagation
Gabriel Azevedo Ferreira, Quentin Bertrand, Charles Maussion +1
Statistical Relational Models and, more recently, Probabilistic Programming, have been making strides towards an integration of logic and probabilistic reasoning. A natural expecta…
Probabilistic Inference Modulo Theories
Rodrigo de Salvo Braz, Ciaran O'Reilly, Vibhav Gogate +1
We present SGDPLL(T), an algorithm that solves (among many other problems) probabilistic inference modulo theories, that is, inference problems over probabilistic models defined vi…
Gibbs Sampling in Open-Universe Stochastic Languages
Nimar S. Arora, Rodrigo de Salvo Braz, Erik B. Sudderth +1
Languages for open-universe probabilistic models (OUPMs) can represent situations with an unknown number of objects and iden- tity uncertainty. While such cases arise in a wide ran…