pymc-devs / pymc

Bayesian Modeling and Probabilistic Programming in Python

py-why / dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

pymc-labs / pymc-marketing

Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.

pgmpy / pgmpy

Python Toolkit for Causal and Probabilistic Reasoning

gempy-project / gempy

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.

bayesian-optimization / BayesianOptimization

A Python implementation of global optimization with gaussian processes.

meta-pytorch / botorch

Bayesian optimization in PyTorch

stan-dev / stan

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.

raphaelvallat / pingouin

Statistical package in Python based on Pandas

jasp-stats / jasp-desktop

JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS

Krishita17 / PhantomTap

A Flipper Zero that stops guessing and starts reasoning: ML-guided RFID/NFC fuzzing & access-control auditing that turns raw card reads into a prioritized, explainable security assessment. Defensive-use only.

arviz-devs / arviz

Exploratory analysis of Bayesian models with Python

paul-buerkner / brms

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

blackjax-devs / blackjax

BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.

bayesflow-org / bayesflow

A Python library for simulation-based inference with deep learning

pymc-devs / pytensor

PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

emdgroup / baybe

Bayesian Optimization and Design of Experiments

pyro-ppl / pyro

Deep universal probabilistic programming with Python and PyTorch

tensorflow / probability

Probabilistic reasoning and statistical analysis in TensorFlow

huawei-noah / HEBO

Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab

pyro-ppl / numpyro

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

avehtari / BDA_course_Aalto

Bayesian Data Analysis course at Aalto

AllenDowney / ThinkBayes2

Text and code for the second edition of Think Bayes, by Allen Downey.

GPflow / GPflow

Gaussian processes in TensorFlow

google / vizier

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

csinva / imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

google / uncertainty-baselines

High-quality implementations of standard and SOTA methods on a variety of tasks.

bambinos / bambi

BAyesian Model-Building Interface (Bambi) in Python.

automl / SMAC3

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

stan-dev / rstan

RStan, the R interface to Stan

FRBNY-DSGE / DSGE.jl

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

sbi-dev / sbi

sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has you covered.

hildensia / bayesian_changepoint_detection

Methods to get the probability of a changepoint in a time series.

cardmagic / classifier

A general classifier module to allow Bayesian and LSI classifications.

easystats / report

:scroll: :tada: Automated reporting of objects in R

google / edward2

A simple probabilistic programming language.

QuantClimate / GPJax

Gaussian processes in JAX and Equinox.

erdogant / bnlearn

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

easystats / bayestestR

:ghost: Utilities for analyzing Bayesian models and posterior distributions

aleximmer / Laplace

Laplace approximations for Deep Learning.

OpSafari / hypoarena

Scientific hypothesis-discovery workbench: grounded hypothesis-evidence graphs, synthetic literature with planted causal chains, generate-debate-evolve loops over pluggable offline adapters, Elo tournaments recovering planted skill order, paraphrase dedup, Bayesian evidence accumulation, reproducible reports. NumPy core, CPU-only torch extra.

nchopin / particles

Sequential Monte Carlo in python

joshuaccchan / bvar-toolkit

MATLAB library for large Bayesian VARs: samplers, shrinkage priors, stochastic volatility, marginal likelihoods and forecasting, with examples, tutorials and the replication packages from joshuachan.org.

TuringLang / Turing.jl

Bayesian inference with probabilistic programming.

SeasonCake / bidking-inference

BidKing product source, self-hostable service components, and a standalone discrete-inference toolkit. MIT-licensed first-party code.