David J. Harris

mcmc-tutorial. Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo

mistnet. stochastic neural networks in R

Davis-dissertation-template. A template for a Markdown/Pandoc template for a UC Davis PhD dissertation or Masters' thesis

Titlebot. R

cran_guide. Recommendations for submitting an R package to CRAN

rosalia. Exact inference for small binary Markov networks

mistnet2. Neural Networks with Latent Random Variables in R

dissertation. My PhD dissertation

geovalidation. Tools for evaluating model performance in a geographic context

homogenization2. TeX

Extreme-events-LDA. R

tutoR. R

als-prognosis. My project for the Insight Health Data Fellowship. Bayesian model for predicting the prognosis of patients with ALS.

bbs-forecasting. Research on forecasting using Breeding Bird Survey data

ais. Annealed importance sampling in R

spotbot.

leafpuppy. Python

davharris.github.com. my home page

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers. aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)