Code for MCPM

An implementation of the model described in Efficient Inference in Multi-task Cox Process Models.

The code was tested on Python 2.7, TensorFlow 1.12 and TensorFlow Probability 0.5

You can download and install MCPM in development mode using:

git clone [email protected]:VirgiAgl/MCPM.git
cd MCPM
python setup.py

The main code is in MCPM/MCPM.py. The folder methods/ contains the functions to run LGCP, MCPM, ICM and Pooling. You will find all the experiments presented in the paper in the folder Experiments/. The results are saved in the folder Data/ when running the experiments. The folder Results_visualisation/ contains the notebooks to get the plots and the performance measures presented in the paper.

You can contact the first author of the paper Virginia Aglietti

The code to support triangular matrices operations under autogp/util/tf_ops was taken from the GPflow repository (Hensman, Matthews et al. GPflow, http://github.com/GPflow/GPflow, 2016).