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Probabilistic Programming

Probabilistic programming languages are designed to describe probabilistic models and then perform inference in those models. PPLs are closely related to graphical models and Bayesian networks, but are more expressive and flexible.

( Image credit: Michael Betancourt )

Papers

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Showing 51–75 of 273 papers

TitleStatusHype
Nonparametric Involutive Markov Chain Monte CarloCode1
Ice Core Dating using Probabilistic ProgrammingCode0
Improved Marginal Unbiased Score Expansion (MUSE) via Implicit DifferentiationCode0
Robust leave-one-out cross-validation for high-dimensional Bayesian modelsCode0
Borch: A Deep Universal Probabilistic Programming LanguageCode0
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development—0
Learning and Compositionality: a Unification Attempt via Connectionist Probabilistic Programming—0
Multi-Model Probabilistic Programming—0
Proceedings 38th International Conference on Logic Programming—0
Language Model CascadesCode2
Towards Plug'n Play Task-Level Autonomy for Robotics Using POMDPs and Generative Models—0
Tensor Program Optimization with Probabilistic Programs—0
Designing Perceptual Puzzles by Differentiating Probabilistic Programs—0
Program Analysis of Probabilistic Programs—0
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming—0
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives—0
A meta-probabilistic-programming language for bisimulation of probabilistic and non-well-founded type systems—0
Compartmental Models for COVID-19 and Control via Policy Interventions—0
A Probabilistic Programming Idiom for Active Knowledge Search—0
Weighted Programming—0
Mixed Nondeterministic-Probabilistic Automata: Blending graphical probabilistic models with nondeterminism—0
Surrogate Likelihoods for Variational Annealed Importance Sampling—0
Simulation Intelligence: Towards a New Generation of Scientific Methods—0
Querying Labelled Data with Scenario Programs for Sim-to-Real Validation—0
Testing Probabilistic Circuits—0
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