Search Results
DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models
Since DynamicPPL is a modular, stand-alone library, any probabilistic programming system written in Julia, such as Turing. jl, can use DynamicPPL to specify models and trace their model parameters.
Efficient Bayesian Structural Equation Modeling in Stan
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof.
Computation
Yaps: Python Frontend to Stan
Stan is a popular probabilistic programming language with a self-contained syntax and semantics that is close to graphical models.
Programming Languages
Mug-STAN: Adapting Image-Language Pretrained Models for General Video Understanding
Large-scale image-language pretrained models, e. g., CLIP, have demonstrated remarkable proficiency in acquiring general multi-modal knowledge through web-scale image-text data.
STAN: Spatio-Temporal Attention Network for Next Location Recommendation
The next location recommendation is at the core of various location-based applications.
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Projection predictive variable selection using Stan+R
This document is additional material to our previous study comparing several strategies for variable subset selection.
Methodology
Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming
We use our compilation scheme to build two new backends for the Stanc3 compiler targeting Pyro and NumPyro.
Visualization in Bayesian workflow
Bayesian data analysis is about more than just computing a posterior distribution, and Bayesian visualization is about more than trace plots of Markov chains.
Methodology Applications
Bayesian workflow for disease transmission modeling in Stan
This tutorial shows how to build, fit, and criticize disease transmission models in Stan, and should be useful to researchers interested in modeling the SARS-CoV-2 pandemic and other infectious diseases in a Bayesian framework.
Computation Quantitative Methods Applications
trialr: Bayesian Clinical Trial Designs in R and Stan
In this article, we explore three methods in detail.
Computation Applications Methodology 97K80
