Live briefing
Everything about Probabilistic programming
Software system for statistical models
Probabilistic programming (PP) is a programming paradigm based on the declarative specification of probabilistic models, for which inference is performed automatically. Probabilistic programming attempts to unify probabilistic modeling and traditional general purpose programming in order to make the former easier and more widely applicable. It can be used to create systems that help make decisions in the face of uncertainty. Programming languages following the probabilistic programming paradigm are referred to as "probabilistic programming languages" (PPLs). Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Probabilistic programmingA 5-minute orientation
- Skim a recent paper: Abduction with probabilistic logic programming under the distribution semanticsInfluential work since 2022
- Pick up a classic book: Artificial intelligenceThe most-reprinted book on the subject
- Read the landmark paper: Probabilistic logic programmingCited 197 times
- Go sideways: List of Julia software and toolsA closely related topic
- Go sideways: Stan (software)A closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Probabilistic logic programming
Probabilistic (logic) programming concepts
Neural probabilistic logic programming in DeepProbLog
On the implementation of the probabilistic logic programming language ProbLog
CP-logic: A language of causal probabilistic events and its relation to logic programming
Probabilistic logic programming with conditional constraints
Combining probabilistic logic programming with the power of maximum entropy
A probabilistic logic programming event calculus
🆕 Influential since 2022
Abduction with probabilistic logic programming under the distribution semantics
Semirings for probabilistic and neuro-symbolic logic programming
“What if?” in Probabilistic Logic Programming
Probabilistic Logic Programming Semantics For Procedural Content Generation
Probabilistic robotic logic programming with hybrid Boolean and Bayesian inference
📚 Books worth reading
Artificial intelligenceStuart J. Russell, Peter Norvig · 1994
Foundations of Probabilistic Logic ProgrammingFabrizio Riguzzi · 2018
Language and Automata Theory and ApplicationsAdrian-Horia Dediu · 2012
Treaty Occupationay ToxicologySuelen Queiroz · 2010
Abstraction, refinement and proof for probabilistic systemsAnnabelle McIver, Charles C. Morgan · 2004
Logic, Language, and ComputationGuram Bezhanishvili · 2013
Logic and Its ApplicationsKamal Lodaya · 2013
Recent Trends in Algebraic Development TechniquesNarciso Martí-Oliet · 2013
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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