Gaussian processes in TensorFlow
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Updated
May 16, 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.
Implementation of Markov Chain Monte Carlo in Python from scratch
MrBayes is a program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models. For documentation and downloading the program, please see the home page:
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
Statistical Rethinking (2nd ed.) with NumPyro
CmdStanR: the R interface to CmdStan
Statistical Rethinking (2nd Ed) with Tensorflow Probability
A C++ library of Markov Chain Monte Carlo (MCMC) methods
DGMs for NLP. A roadmap.
Manifold Markov chain Monte Carlo methods in Python
Code for "A-NICE-MC: Adversarial Training for MCMC"
R package for statistical inference using partially observed Markov processes
High-performance Bayesian Data Analysis on the GPU in Clojure
Diffusive Nested Sampling
GammaRay: a graphical interface to GSLib and other geomodeling algorithms. *NEW* in May, 6th: Drift analysis.
Bayesian Inference of State Space Models
Affine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler
Python implementation of MATLAB toolbox "mcmcstat"
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