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Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Bayesian inference with probabilistic programming.
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
Manifold Markov chain Monte Carlo methods in Python
A native Julia code for lattice QCD with dynamical fermions in 4 dimension.
Bayesian Generalized Linear models using `@formula` syntax.
A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.
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 details: "A Primer on Bayesian Neural Networks: Review and Debates"
Lightweight MCMC sampling for PyTorch Models aka My Corona Project
AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.
A pure Python client library for the IBM Z HMC Web Services API
tmLQCD is a freely available software suite providing a set of tools to be used in lattice QCD simulations. This is mainly a HMC implementation (including PHMC and RHMC) for Wilson, Wilson Clover and Wilson twisted mass fermions and inverter for different versions of the Dirac operator. The code is fully parallelised and ships with optimisations for various modern architectures, such as commodity PC clusters and the Blue Gene family.
Hybrid Memory Cube Simulation & Research Infrastructure
A Prometheus exporter for the IBM Z HMC
An Ansible collection for the IBM Z HMC
Code accompanying the paper 'Manifold MCMC methods for Bayesian inference in a wide class of diffusion models'
Utilities of gauge fields
Bayesian deep learning experiments
Accompanying code for 'Manifold lifting: scaling MCMC to the vanishing noise regime'
Inference in differentiable generative models
OpenShift on IBM PowerVM servers managed using HMC
An experimental Python package for learning Bayesian Neural Network.
Used in Deep Machine Learning and Lattice Quantum Chromodynamics
5scheduler.io - Course Scheduler for the 5Cs
Dirac operators for lattice QCD with Julia
A GoLang client library for the IBM Z HMC Web Services API