286 Open source projects that are alternatives of or similar to Pymc3

Probabilistic Programming with Gaussian processes in Julia

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.

Infer the gender of an individual based on their name.

Lecture notes on Bayesian deep learning

Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

🎓 Uni-Bonn Decision Analysis graduate course, lectures and materials

rstanarm R package for Bayesian applied regression modeling

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

A C++ library of Markov Chain Monte Carlo (MCMC) methods

Deodorant: Solving the problems of Bayesian Optimization

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

Helper functions for brmsfit objects (DEPRECATED)

Application of the L2HMC algorithm to simulations in lattice QCD.

Lagrangian VAE

Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

Open-source Python library for statistical analysis of randomised control trials (A/B tests)

Benchmarks of Bayesian Nonparametric models in Turing and other PPLs

Implementations of single and multi-ellipsoid nested sampling

Pieces of code that have appeared on my blog with a focus on stochastic simulations.

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen

BAS R package https://merliseclyde.github.io/BAS/

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

bayesplot R package for plotting Bayesian models

Find nodes in hierarchical clustering that are statistically significant

Bayesian inference for Gaussian mixture model with some novel algorithms

Stanマニュアルの日本語への翻訳プロジェクト

A multi-planet Radial Velocity and Transit modelling software

Code for the paper Implicit Weight Uncertainty in Neural Networks

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

nway -- Bayesian cross-matching of astronomical catalogues

🦊 Kitsu seasonal anime trends

Parallel nested sampling

Estimating effective elastic thickness of the lithosphere

Bitmap generation from a single example with convolutions and MCMC

How to do Bayesian statistical modelling using numpy and PyMC3

Documentation, models and code relating to the 3rd edition of the textbook Stochastic Modelling for Systems Biology

Hierarchical, multi-label topic modelling with LDA

The repo for LFQ-Analyst

Specifying and executing multiverse analysis

Noisy network measurement with stan

A toy model of Friston's active inference in Tensorflow

Query2Report is a simple open source business intelligence platform that allows users to build report/dashboard for business analytics or enterprise reporting

PixelVAE with or without regularization

CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations

Implementation of Sequential Attend, Infer, Repeat (SQAIR)

The Trendiness of Trends

Variational autoencoders for collaborative filtering

Implementing MCMC sampling from scratch in R for various Bayesian models

We got a stew going!

UAI 2015. Kernel-based just-in-time learning for expectation propagation

Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

PyTorch Implementations of Dropout Variants

A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"

Abstractive opinion summarization system (SelSum) and the largest dataset of Amazon product summaries (AmaSum). EMNLP 2021 conference paper.