stan-dev / posteriordb-python
☆20Updated last month
Related projects ⓘ
Alternatives and complementary repositories for posteriordb-python
- Exploring and eliciting probability distributions☆88Updated this week
- Self-tuning HMC algorithms and evaluations☆18Updated last month
- Bayesian Conjugate Models in Python☆24Updated this week
- ☆82Updated this week
- State of the art inference for your bayesian models.☆163Updated last month
- Python wrapper for nuts-rs☆123Updated this week
- Database with posteriors of interest for Bayesian inference☆181Updated 2 months ago
- Bayesian inference and posterior analysis for Python☆42Updated 10 months ago
- Tools for an Aesara-based PPL.☆64Updated last week
- Bayesian Regression Models in Pyro☆70Updated 3 months ago
- BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.☆95Updated last week
- AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.☆39Updated last year
- ☆87Updated this week
- Statistical Rethinking: A Bayesian Course Using Python and NumPyro☆87Updated 3 years ago
- Just a little MCMC☆217Updated 4 months ago
- Markov chain Monte Carlo general, and Hamiltonian Monte Carlo specific, diagnostics for Stan☆78Updated last month
- Hidden Markov models in PyMC3☆96Updated 7 months ago
- A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.☆52Updated 3 months ago
- CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan progra…☆153Updated last month
- Tutorials and sampling algorithm comparisons☆68Updated this week
- A backend for storing MCMC draws.☆14Updated last week
- The tiniest of Gaussian Process libraries☆295Updated this week
- A colourful collection of codes and notebooks, like Planet Sakaar☆55Updated last year
- Examples of PyMC models, including a library of Jupyter notebooks.☆288Updated last month
- Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX.☆325Updated 7 months ago
- A simple library to run variational inference on Stan models.☆26Updated last year
- Compares Stan, PyMC, and PyMC + JAX numpyro sampler on a model for tennis☆29Updated last year
- Educational resources☆100Updated 2 years ago
- A system for Bayesian estimation of state space models using PyMC☆33Updated last year
- Implementation of simulation based calibration for PyMC and Bambi☆32Updated 2 months ago