Example code for using Transport Monte Carlo --- using random transport plan and optimization to rapidly estimate the posterior distribution

1. Sampling from a Normal Mixture: https://nbviewer.jupyter.org/github/leoduan/TransportMonteCarlo/blob/master/gaussianMixtureTMC.ipynb

2. Sampling from a multi-modal distribution (Liang 2005): https://nbviewer.jupyter.org/github/leoduan/TransportMonteCarlo/blob/master/MultimodalTMC.ipynb

3. High-dimensional regression using the regularized horseshoe prior (Piironen and Vehtari 2017) : https://nbviewer.jupyter.org/github/leoduan/TransportMonteCarlo/blob/master/regularizedHorseshoe.ipynb

4. Binary adjacency matrix estimation under degree regularization: https://github.com/leoduan/TransportMonteCarlo/blob/master/edgeSamplingUnderDegreeReg.ipynb

For other target distribution, simply modify the log-prior-likelihood function.

For reference, see Leo L. Duan. Transport Monte Carlo 2019+. http://arxiv.org/abs/1907.10448