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 ...

When you’re programming an artificial intelligence application, you’re usually building statistical models that output discrete values. Is that image a human face? Whose face is it? Is that face ...

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 ...

An app developed by Gamalon recognizes objects after seeing a few examples. A learning program recognizes simpler concepts such as lines and rectangles. Machine learning is becoming extremely powerful ...

Probabilistic programming is a recent and extremely dynamic field of research which lies at the intersection of statistical machine learning and programming language theory. Probabilistic programming ...