A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
-
Updated
Jul 10, 2024 - Python
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
PyStan, the Python interface to Stan
A surface language for programming Stan models using python syntax
A sklearn style interface to Stan regression models
Phylogenetic inference using Stan
Bayesian Inferential Regression for Differential Microbiome Analysis
Code for "Reconstruction of plant--pollinator networks from observational data"
A simple library to run variational inference on Stan models.
Bayesian models of football leagues
Gaussian processes on graphs and lattices in Stan and pytorch.
Unofficial implementation of STAN paper published at ISBI 2020 by researchers from University of Idaho using Tensorflow Keras 2.0.
Source code and data for the EDM 2022 paper
Structural time series modeling and forecasting in Python
scikit-learn wrapper for generalized linear mixed model methods in R
GRB triangulation via non-stationary time-series models
Undermining the integrity of an office prediction contest
Add a description, image, and links to the stan topic page so that developers can more easily learn about it.
To associate your repository with the stan topic, visit your repo's landing page and select "manage topics."