Probabilistic programming has emerged as a powerful paradigm for constructing and analysing statistical models by combining the expressiveness of modern programming languages with the rigour of ...

Most recent advances in artificial intelligence—such as mobile apps that convert speech to text—are the result of machine learning, in which computers are turned loose on huge data sets to look for ...

確率的プログラミング（Probabilistic Programming: PP）は、確率的モデルを指定し、そのモデルに対する推論を自動的に行うプログラミングパラダイムである いくつかのPPLが活発に開発されており、その中にはベータテスト中のものもある。最も人気のあるツール ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Martin Kleppmann, an associate professor at ...

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 programs are usual functional or imperative programs with two added constructs: (1) the ability to draw values at random from distributions, and (2) the ability to condition values of ...

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 ...

Probabilistic programming is an approach to computing based on the idea that probabilistic models can be naturally and efficiently represented as executable code. This idea has enabled researchers to ...

Recent progress on probabilistic modeling and statistical learning, coupled with the availability of large training datasets, has led to remarkable progress in computer vision. Generative ...

In his 1982 famous paper, Richard Feynman wrote that "we could have a computer that simulates a probabilistic theory", in particular a quantum computer, which uses quantum bits as the hardware ...