Probabilistic algorithms for doing Markov chain, Monte Carlo and variational inferencing; and End-to-end examples with scripts and tutorial notebooks for programming in TensorFlow probability.

Probabilistic Programming is a way of defining probabilistic models by overloading the operations in standard programming language to have probabilistic meanings. The goal is to specify probabilistic ...

Probabilistic Programming and Inference Algorithms Publication Trend The graph below shows the total number of publications each year in Probabilistic Programming and Inference Algorithms.

In a probabilistic programming language, the heavy lifting is done by the inference algorithm -- the algorithm that continuously readjusts probabilities on the basis of new pieces of training data.

In a probabilistic programming language, the heavy lifting is done by the inference algorithm—the algorithm that continuously readjusts probabilities on the basis of new pieces of training data.

The choice of PyMC as the probabilistic programming language is two-fold. As of this writing, there is currently no central resource for examples and explanations in the PyMC universe. The official ...

"Probabilistic" programming can instruct a computer using just 50 lines of code to complete a task that used to take thousands of lines, researchers say. New programming languages are being ...

Ron Shamir, Probabilistic Analysis in Linear Programming, Statistical Science, Vol. 8, No. 1, Report from the Committee on Applied and Theoretical Statistics of the National Research Council on ...

Probabilistic Programming 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 ...