The repo contains the source code for the algorithms and results described in the paper “Learning multivariate temporal point processes via the time-change theorem” by Guilherme Augusto Zagatti, See-Kiong Ng, and Stéphane Bressan.
The repo is organised according to the following source tree.
.
├── bin
│ ├── benchmark.py # main entry point for benchmarking models trained from the CLI
│ ├── evaluate.py # main entry point for evaluating models trained from the CLI
│ ├── experiment.py # main entry point for training from the CLI
│ ├── run_multiple.py # run multiple experiments and validations
│ └── sahp_to_ttpp.py # convert SAHP data to TTPP format
├── multittpp
│ ├── config.py # default configurations
│ ├── data.py # data loaders
│ ├── flows # implementation of triangular maps for multi TPP
│ │ ├── affine.py
│ │ ├── base.py
│ │ ├── block_diagonal.py
│ │ ├── cumsum.py
│ │ ├── exp.py
│ │ ├── __init__.py
│ │ ├── sigmoid.py
│ │ ├── spline.py
│ │ ├── transformer.py
│ │ └── utils.py
│ ├── __init__.py
│ ├── models # implementation of multi TPP models
│ │ ├── base.py # base model class
│ │ └── __init__.py # concrete models
│ ├── plot.py # plot helpers
│ ├── trainer.py # trainer class which manages all training and validation routines
│ └── utils.py # miscellaneous utilities
├── notebooks
│ └── plots.org # paper plots
├── README.org
├── requirements.txt
├── setup.py
└── tests # unit tests
├── conftest.py
├── test_flows.py # test all flows are invertible
└── test_models.py
6 directories, 30 files