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