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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
A pure Python client library for the IBM Z HMC Web Services API
AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.
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.
A Prometheus exporter for the IBM Z HMC
Hybrid Memory Cube Simulation & Research Infrastructure
Utilities of gauge fields
An Ansible collection for the IBM Z HMC
A Shiny app to help people learn (and play with) Hamiltonian Monte Carlo
Code accompanying the paper 'Manifold MCMC methods for Bayesian inference in a wide class of diffusion models'
Bayesian deep learning experiments
Inference in differentiable generative models
Accompanying code for 'Manifold lifting: scaling MCMC to the vanishing noise regime'
HMCi is a utility that collects metrics from one or more IBM Power Hardware Management Consoles (HMC), without the need to install agents on logical partitions / virtual machines running on the IBM Power systems.
OpenShift on IBM PowerVM servers managed using HMC
An experimental Python package for learning Bayesian Neural Network.
Dirac operators for lattice QCD with Julia
Used in Deep Machine Learning and Lattice Quantum Chromodynamics
5scheduler.io - Course Scheduler for the 5Cs