Gaussian processes in TensorFlow
-
Updated
Jun 13, 2024 - Python
Gaussian processes in TensorFlow
Generating Neural Spatial Interaction Tables
Machine learning algorithms for many-body quantum systems
Generalised Bayesian inversion framework
Python library for the evaluation of simulation data. The library provides functionalities to load simulation results into Python, to perform standard evaluation algorithms for Markov Chain Monte Carlo algorithms. It further can be used to generate a pytorch dataset from the simulation data.
Python implementation of the cellular automata model corresponding to Lange, Schmied et. al.
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
Finding a cure through using Python libraries and dependencies for support.
Likelihood for LiteBIRD
A straightforward Bayesian data fitting library
Manifold Markov chain Monte Carlo methods in Python
Markov Chain Monte Carlo MCMC methods are implemented in various languages (including R, Python, Julia, Matlab)
Sujet de grand oral en maths, ce programme python permet de calculer la probabilité de chaque case du jeu Monopoly en utilisant les chaines de Markov et la méthode de Monte Carlo
Monte is a set of Monte Carlo methods in Python. The package is written to be flexible, clear to understand and encompass variety of Monte Carlo methods.
A toolbox for inference of mixture models
Lightweight Bayesian deep learning library for fast prototyping based on PyTorch
Repository for my research project on Inverse Contextual Bandits
Bayesian Structured Time Series Analysis with Parallel Tempering for Stock Market Prediction
Add a description, image, and links to the markov-chain-monte-carlo topic page so that developers can more easily learn about it.
To associate your repository with the markov-chain-monte-carlo topic, visit your repo's landing page and select "manage topics."