## Reproducible Research

- Python (TensorFlow) code for "Semi-implicit variational inference" can be found HERE
- Matlab & C code for "Multimodal Poisson gamma belief network" can be found HERE
- Matlab code for "Deep latent Dirichlet allocation with topic-layer-adaptive stochastic gradient Riemannian MCMC" can be found HERE
- R code for "BNP-Seq: Bayesian nonparametric differential expression analysis of sequencing count data" can be found HERE
- Matlab & C code for "Negative Binomial Factor Analysis" can be found HERE
- Matlab code for "Fast simulation of hyperplane-truncated multivariate normal distributions" can be found HERE
- Python code for "Poissonâ€“gamma dynamical systems" can be found HERE
- Matlab & C code for gamma belief networks can be found HERE
- Matlab & C code for "Frequency of frequencies distributions and size dependent exchangeable random partitions" can be found HERE
- Matlab code for random count matrices and naive Bayes classifiers using negative binomial processes can be found HERE
- Matlab code for Infinite Edge Partition Models (EPMs) can be found HERE
- Collapsed Gibbs sampling for the beta-negative binomial process can be found HERE
- Matlab code for a variety of negative binomial process topic models (including the gamma-NBP and beta-NBP, 08/2012 version) can be found HERE
- Gibbs sampling Matlab code for "Lognormal and Gamma Mixed Negative Binomial Regression" (02/16/2013 version) can be found HERE
- Variational Bayes Matlab code for the negative binomial distribution (10/13/2012 version, updated in Aug 2016) can be found HERE
- Gibbs sampling Matlab code for the negative binomial distribution (10/12/2012 version) can be found HERE
- BPFA Gray-scale, RGB and Hyperspectral image inpainting & denoising code (04/15/2010 version, last update 02/16/2012) can be found HERE
- BPFA Gray-scale and RGB image denoising code (last update 04/15/2010) can be found HERE
- Matlab codes and inference equations for "Non-Parametric Bayesian dictionary learning for sparse image representations" can be found HERE

© March 2018 Mingyuan Zhou