Deep universal probabilistic programming with Python and PyTorch
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Bayesian Data Analysis course at Aalto
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
A general-purpose probabilistic programming system with programmable inference
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
Bayesian Data Analysis demos for Python
Seminars DeepBayes Summer School 2018
📜 🎉 Automated reporting of objects in R
How to do Bayesian statistical modelling using numpy and PyMC3
👻 Utilities for analyzing Bayesian models and posterior distributions
Bayesian Data Analysis demos for R
PyTorch implementation of bayesian neural network [torchbnn]
A collection of Bayesian data analysis recipes using PyMC3
Bayesian Deep Learning: A Survey
Python package for Bayesian Machine Learning with scikit-learn API
A python library for Bayesian time series modeling
To associate your repository with the bayesian topic, visit your repo's landing page and select "manage topics."