pymc-devs / pymc
Bayesian Modeling and Probabilistic Programming in Python
pymc-devs / pymc
pyro-ppl / pyro
Deep universal probabilistic programming with Python and PyTorch
bayesian-optimization / BayesianOptimization
A Python implementation of global optimization with gaussian processes.
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.
tensorflow / probability
Probabilistic reasoning and statistical analysis in TensorFlow
meta-pytorch / botorch
Bayesian optimization in PyTorch
pgmpy / pgmpy
Python Toolkit for Causal and Probabilistic Reasoning
huawei-noah / HEBO
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
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.
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
TuringLang / Turing.jl
Bayesian inference with probabilistic programming.
AllenDowney / ThinkBayes2
Text and code for the second edition of Think Bayes, by Allen Downey.
raphaelvallat / pingouin
Statistical package in Python based on Pandas
GPflow / GPflow
Gaussian processes in TensorFlow
arviz-devs / arviz
Exploratory analysis of Bayesian models with Python
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.
paul-buerkner / brms
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
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.
bambinos / bambi
BAyesian Model-Building Interface (Bambi) in Python.
pymc-labs / pymc-marketing
Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
automl / SMAC3
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
blackjax-devs / blackjax
BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.
stan-dev / rstan
RStan, the R interface to Stan
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
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.
bayesflow-org / bayesflow
A Python library for simulation-based inference with deep learning
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.
pymc-devs / pytensor
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
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.
emdgroup / baybe
Bayesian Optimization and Design of Experiments
nchopin / particles
Sequential Monte Carlo in python
SeasonCake / bidking-inference
BidKing product source, self-hostable service components, and a standalone discrete-inference toolkit. MIT-licensed first-party code.
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.
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.