GPstuff - Gaussian process models for Bayesian analysis

MCMC toolbox for Matlab

Bayesian Data Analysis demos for Matlab/Octave

A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural networks and hierarchical distribution (ICML 2018).

machine learning

AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)

Codes related to the publication Gaussian mixture Markov chain Monte Carlo method for linear seismic inversion

CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations

MCMC simulation using Gibbs sampling.

Monte Carlo simulations and Point Estimate Methods

Exact Hamiltonian Monte Carlo Sampler for Truncated Multivariate Gaussians

Subset simulation is a method of estimating low probability events. Here I adapt SS to perform well with correlated inputs.

Yet Another Matlab MCMC code

Code for training and validation of ion channel models fitted to sine-wave based voltage clamp data

Localization of brain sources measured by EEG using 3 approaches: Gibbs sampler (Markov chain Monte Carlo algorithm), Minimum Norm Estimates (MNE) and Source Imaging based on Structured Sparsity (SISSY)

Synthetic Data Generation by Markov Chain Monte Carlo (MCMC)

course project of Probability and Stochastic Processes (2) of EE, Tsinghua University.

Inverse Problems Project: Deconvolution of a Sparse Signal - 3rd year Electronics Engineering and Signal Processing at INP-ENSEEIHT

Probabilistic ODE model structure inference using MCMC

Bayesian network modeling and inference