SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 226–250 of 273 papers

TitleStatusHype
Complex Coordinate-Based Meta-Analysis with Probabilistic Programming—0
Composing inference algorithms as program transformations—0
Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations—0
Consistent Kernel Mean Estimation for Functions of Random Variables—0
Data-driven Sequential Monte Carlo in Probabilistic Programming—0
Data Petri Nets meet Probabilistic Programming (Extended version)—0
Decision-Making with Complex Data Structures using Probabilistic Programming—0
Declarative Modeling and Bayesian Inference of Dark Matter Halos—0
Declarative Probabilistic Logic Programming in Discrete-Continuous Domains—0
Declarative Statistical Modeling with Datalog—0
Deep Probabilistic Programming—0
Deep Probabilistic Programming Languages: A Qualitative Study—0
Probabilistic Surrogate Networks for Simulators with Unbounded Randomness—0
DeepRV: pre-trained spatial priors for accelerated disease mapping—0
Dependency Parsing for Weibo: An Efficient Probabilistic Logic Programming Approach—0
Deployable probabilistic programming—0
Designing Perceptual Puzzles by Differentiating Probabilistic Programs—0
Detecting and Quantifying Malicious Activity with Simulation-based Inference—0
Detecting Parameter Symmetries in Probabilistic Models—0
Dimensionality Reduction as Probabilistic Inference—0
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms—0
Doubly Bayesian Optimization—0
Effect Handling for Composable Program Transformations in Edward2—0
Efficient Incremental Belief Updates Using Weighted Virtual Observations—0
Efficient Inference Amortization in Graphical Models using Structured Continuous Conditional Normalizing Flows—0
Show:102550
← PrevPage 10 of 11Next →

No leaderboard results yet.