The Python ensemble sampling toolkit for affine-invariant MCMC
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Updated
Mar 3, 2025 - Python
The Python ensemble sampling toolkit for affine-invariant MCMC
⚡️ zeus: Lightning Fast MCMC ⚡️
Code for Bayesian Analysis
pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation
Bayesian inference for Gaussian mixture model with some novel algorithms
Markov Chain Monte Carlo MCMC methods are implemented in various languages (including R, Python, Julia, Matlab)
Bayesian Inference. Parallel implementations of DREAM, DE-MC and DRAM.
cronus: MCMC + MPI MADE EASY
Python information for Adaptive Rejection Sampling (ARS)
Python implementation (from scratch) of some MCMC samplers that can leverage pyTorch's autodifferentiation (with examples).
Problem Solving With AI Approaches: Heuristic Searches, Statistical Classifications
Code for the ICLR 2025 paper: "Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks"
My works for EE 511 - Simulation Methods For Stochastic Systems - Spring 2018 - Graduate Coursework at USC - Dr. Osonde A. Osoba
Hamiltonian Monte Carlo (HMC) sampling method in Python3, based on the original paper: Simon Duane, Anthony D. Kennedy, Brian J. Pendleton and Duncan Roweth (1987). "Hybrid Monte Carlo". Physics Letters B. 195 (2): 216–222.
Parallel Bayesian inference for decomposable graphical models.
Bayesian inference on monthly sunspot data to find Jupiter's influence
Markov Chain Monte Carlo methods.
FireFly - A Bayesian approach to source finding in Astronomical data.
Running Monte Carlo - Markov Chain algorithm on synthesized spectral models made by CLOUDY to compare them with data from CECILIA survey
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