Fully Bayesian inference for discovering latent network structure underlying Hawkes processes. This work was originally published in:

Linderman, Scott W. and Adams, Ryan P. Discovering Latent Network Structure in Point Process Data. International Conference on Machine Learning (ICML), 2014.

To check out, run git clone --recursive git@github.com:slinderman/pyhawkes.git

To compile the cython code, run python setup.py build_ext --inplace

This codebase corresponds to a new parameterization of the Hawkes process model that will be outlined in a forthcoming paper. It is considerably cleaner than the old CUDA version, and is still pretty fast with the Cython+OMP extensions.