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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.
AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.
Lightweight MCMC sampling for PyTorch Models aka My Corona Project
A pure Python client library for the IBM Z HMC Web Services API
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"
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
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'
A Prometheus exporter for the IBM Z HMC
Utilities of gauge fields
Bayesian deep learning experiments
Accompanying code for 'Manifold lifting: scaling MCMC to the vanishing noise regime'
5scheduler.io - Course Scheduler for the 5Cs
Inference in differentiable generative models
An experimental Python package for learning Bayesian Neural Network.
Used in Deep Machine Learning and Lattice Quantum Chromodynamics
OpenShift on IBM PowerVM servers managed using HMC
Dirac operators for lattice QCD with Julia
A GoLang client library for the IBM Z HMC Web Services API
Ruby software to create reports about AIX Power environements (HMC, Power servers, VIOSes, NIM servers etc). Next version will allow also manage it. This API is unstable, stable version is expected in September 2020