Probabilistic Programming

The programming languages and machine learning communities have, over the last few years, developed a shared set of research interests under the umbrella of probabilistic programming. The idea is that we might be able to “export” powerful PL concepts like abstraction and reuse to statistical modeling, which is currently an arcane and arduous task.

Probabilistic Programming Probabilistic Programming The programming languages and machine learning communities have, over the last few years, developed a shared set of research interests under the umbrella of probabilistic programming . The idea is that we might be able to “export” powerful PL concepts like abstraction and reuse to statistical modeling, which is currently an arcane and arduous task. (You may want to read the most recent version of these lecture notes. The source is on GitHub . If you notice any mistakes, please open a pull request.) 1 .  What and Why 1.1 .&#8

related reading

• Bayesian programming - Wikipediaen.wikipedia.org
• Learnable Programmingworrydream.com
• ProbabilisticRobotics.pdfdocs.ufpr.br
• Deep Reinforcement Learning: Pong from Pixelskarpathy.github.io
• Interpretations of Probability (Stanford Encyclopedia of Philosophy)plato.stanford.edu
• Applying Probabilistic Programming to Affective Computingarxiv.org
• Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Reviewarxiv.org
• Contentsermongroup.github.io
• Probabilities are not the right concept — LessWronglesswrong.com
• Language Modelinglena-voita.github.io
• The Value of Probabilistic Thinking: Spies, Crime, and Lightning Strikesfs.blog
• Imprecise Probabilities (Stanford Encyclopedia of Philosophy)plato.stanford.edu