Gaussian processes in TensorFlow
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Updated
Jun 3, 2024 - Python
Gaussian processes in TensorFlow
Machine learning algorithms for many-body quantum systems
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
Manifold Markov chain Monte Carlo methods in Python
Exploration of metropolis-hastings (local) and Uli Wolff (cluster) algorithms on the Ising Model
Bayesian Deep Learning with Stochastic Gradient MCMC Methods
A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.
Accelerating Monte Carlo methods for Bayesian inference in dynamical models
A straightforward Bayesian data fitting library
A toolbox for inference of mixture models
Classical models implemented from a Markov operator's perspective
BISIP | Bayesian inversion of spectral induced polarization laboratory data
Markov Chain Monte Carlo MCMC methods are implemented in various languages (including R, Python, Julia, Matlab)
This repo implements Robert, Wu, Stoehr, CP Robert - 2019 (https://arxiv.org/abs/1810.04449) algorithms eHMC and prHMC
This repo contains the code of Transitional Markov chain Monte Carlo algorithm
Discrete Array Variable Reversible jump MCMC
Statistical simulation and analysis of oil & gas productivity from South Dakota well-by-well production time series
Generalised Bayesian inversion framework
Replica Exchange Monte Carlo using PyStan2
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