pymc-learn: Practical probabilistic machine learning in Python

Fast & scalable MCMC for all your exoplanet needs!

Hidden Markov models in PyMC3

Work-In-Progress: conjoint analysis in Python

「Pythonによるベイズ統計学入門」の正誤表とPythonコード

Differentiable interface to FEniCS for PyMC3

Asteroid Thermal Modeling

Marketing attribution using Bayesian credible sets and regression methods

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

Markov Chain Monte Carlo binary network optimization

Bayesian Gene Heritability Analysis from GWAS summary statistics

Demo how one could use PyMC3 to learn the structure of a Bayesian network.

Comparing the performance of the probabilistic programming languages PyMC3 and Stan.

A sphinx primer for ArviZ and PyMC contributors

Statistical Causal Inference Library using Bayesian Mixed LiNGAM and WBIC

Some work I did for an interview for a job as a data scientist optimisation specialist

Statistical causal discovery based on cyclic model

Simulating the detection of millihertz (mHz) gravitational waves (GWs) from astrophysical sources by a Storage Ring Gravitational-wave Observatory (SRGO).

Example code to perform linear mixed effects regression in a Bayesian setting using the PyMc3 framework

Deep hierarchical models combined with Markov random fields.