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 ...

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 ...

Thomas Dullien discusses how language design choices impact performance, how Google's monorepo culture and Amazon's two-pizza-team culture impact code efficiency, and why statistical variance is an ...

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 ...

Okay, I have to admit, I live in something of a programming language filter bubble—among people I know, probabilistic programming languages are a regular topic of conversation. So I was quite ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...