Probabilistic programming languages (PPLs) have emerged as a transformative tool for expressing complex statistical models and automating inference procedures. By integrating probability theory into ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Researchers can demonstrate that on some standard computer-vision tasks, short programs -- less than 50 lines long -- written in a probabilistic programming language are competitive with conventional ...