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Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Created
2019-02-13
1,268 commits to master branch, last one 3 days ago
Bayesian inference with probabilistic programming.
Created
2016-04-29
3,411 commits to master branch, last one 2 days ago
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
hmc
mcmc
sgld
pytorch
mc-dropout
regression
uncertainty
deep-learning
classification
bayes-by-backprop
langevin-dynamics
bayesian-inference
approximate-inference
reproducible-research
variational-inference
bayesian-neural-networks
uncertainty-neural-networks
local-reparametrization-trick
out-of-distribution-detection
kronecker-factored-approximation
Created
2019-03-11
86 commits to master branch, last one about a year ago
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
Created
2019-10-04
72 commits to master branch, last one 5 months ago
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Created
2016-11-02
415 commits to master branch, last one 16 days ago
Manifold Markov chain Monte Carlo methods in Python
Created
2016-02-25
454 commits to main branch, last one 7 days ago
A C++ library of Markov Chain Monte Carlo (MCMC) methods
Created
2017-08-12
85 commits to master branch, last one 11 months ago
A native Julia code for lattice QCD with dynamical fermions in 4 dimension.
Created
2020-12-01
589 commits to master branch, last one 20 days ago
Bayesian Generalized Linear models using `@formula` syntax.
Created
2021-11-03
104 commits to main branch, last one 2 months ago
Application of the L2HMC algorithm to simulations in lattice QCD.
Created
2019-03-21
6,366 commits to main branch, last one about a year ago
A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.
Created
2019-12-08
111 commits to master branch, last one 3 years ago
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 ...
Created
2023-01-16
18 commits to main branch, last one about a year ago
AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.
Created
2021-12-14
107 commits to main branch, last one about a year ago