Popular GitHub Repositories for Mcmc

Bayesian Modeling and Probabilistic Programming in Python

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Bayesian inference with probabilistic programming.

Boltzmann Machines in TensorFlow with examples

DGMs for NLP. A roadmap.

Normalizing-flow enhanced sampling package for probabilistic inference in Jax

Collection of probabilistic models and inference algorithms

GPstuff - Gaussian process models for Bayesian analysis

Code for "A-NICE-MC: Adversarial Training for MCMC"

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

Lightweight library of stochastic gradient MCMC algorithms written in JAX.

pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation

Directed evolution of proteins in sequence space with gradients

Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.

A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural networks and hierarchical distribution (ICML 2018).

A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"

Automatic forecasting and Bayesian modeling for time series with Stan

Full Bayesian Inference for Hidden Markov Models

德州扑克AI软件MasterAI，专注于多人（单人或多人）德州扑克不完全信息博弈。MasterAI 2.0版本是在MasterAI 1.0的基础上迭代改进的算法，它结合了通用的强化学习和搜索技术，在无限注德州扑克一对一游戏中实现了超越人类的表现。现出售AI源码。联系方式：Telegram：@xuzongbin001；邮箱：masterai918@gmail.com

A fully Bayesian implementation of sequential model-based optimization