bayesian-methods
There are 383 repositories under bayesian-methods topic.
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
blei-lab/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
tensorflow/probability
Probabilistic reasoning and statistical analysis in TensorFlow
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.
avehtari/BDA_course_Aalto
Bayesian Data Analysis course at Aalto
uber/orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
krasserm/bayesian-machine-learning
Notebooks about Bayesian methods for machine learning
google/uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
google/edward2
A simple probabilistic programming language.
ericmjl/bayesian-analysis-recipes
A collection of Bayesian data analysis recipes using PyMC3
stan-dev/rstanarm
rstanarm R package for Bayesian applied regression modeling
nansencenter/DAPPER
Data Assimilation with Python: a Package for Experimental Research
markovmodel/PyEMMA
🚂 Python API for Emma's Markov Model Algorithms 🚂
FrankPortman/bayesAB
🐢 bayesAB: Fast Bayesian Methods for A/B Testing
tpapp/DynamicHMC.jl
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
pints-team/pints
Probabilistic Inference on Noisy Time Series
Joshuaalbert/jaxns
Probabilistic Programming and Nested sampling in JAX
BayesWatch/deep-kernel-transfer
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
stan-dev/shinystan
shinystan R package and ShinyStan GUI
nimble-dev/nimble
The base NIMBLE package for R
brendanhasz/probflow
A Python package for building Bayesian models with TensorFlow or PyTorch
nansencenter/DA-tutorials
Tutorials on data assimilation (DA) and the EnKF
fehiepsi/rethinking-pyro
Statistical Rethinking with PyTorch and Pyro
grinisrit/noa
Differentiable Programming Algorithms in Modern C++
stan-dev/loo
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
biaslab/ForneyLab.jl
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
gbosquechacon/statrethink_course_in_pymc3
Statistical Rethinking course in pymc3
pyxu-org/pyxu
Modular and scalable computational imaging in Python with GPU/out-of-core computing.
Shmuma/rethinking-2ed-julia
Port of Statistical Rethinking (2nd edition) code to Julia
amirabbasasadi/mathematics-computerscience-courses
A collection of awesome mathematics and computer science courses
jonsedar/pymc3_vs_pystan
Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg
rohinarora/EECE5644-Machine_Learning
Graduate course on Machine Learning
amidst/toolbox
A Java Toolbox for Scalable Probabilistic Machine Learning
lawmurray/Birch
A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.
jbrea/BayesianOptimization.jl
Bayesian optimization for Julia
google-research/hyperbo
Pre-trained Gaussian processes for Bayesian optimization