
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling
We present new techniques for automatically constructing probabilistic p...
read it

Using probabilistic programs as proposals
Monte Carlo inference has asymptotic guarantees, but can be slow when us...
read it

AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Approximate probabilistic inference algorithms are central to many field...
read it

Probabilistic programs for inferring the goals of autonomous agents
Intelligent systems sometimes need to infer the probable goals of people...
read it

Encapsulating models and approximate inference programs in probabilistic modules
This paper introduces the probabilistic module interface, which allows e...
read it

Measuring the nonasymptotic convergence of sequential Monte Carlo samplers using probabilistic programming
A key limitation of sampling algorithms for approximate inference is tha...
read it

Quantifying the probable approximation error of probabilistic inference programs
This paper introduces a new technique for quantifying the approximation ...
read it
Marco F. CusumanoTowner
is this you? claim profile