ICML 2018: "Adversarial Time-to-Event Modeling"
This repository contains the TensorFlow code to replicate experiments in our paper Adversarial Time-to-Event Modeling (ICML 2018):
@inproceedings{chapfuwa2018adversarial,
title={Adversarial Time-to-Event Modeling},
author={Chapfuwa, Paidamoyo and Tao, Chenyang and Li, Chunyuan and Page, Courtney and Goldstein, Benjamin and Carin, Lawrence and Henao, Ricardo},
booktitle={ICML},
year={2018}
}
This project is maintained by Paidamoyo Chapfuwa. Please contact [email protected] for any relevant issues.
The code is implemented with the following dependencies:
pip install -r requirements.txt
We consider the following datasets:
For convenience, we provide pre-processing scripts of all datasets (except EHR). In addition, the data directory contains downloaded Flchain and SUPPORT datasets.
The code consists of 3 models: DATE, DATE-AE and DRAFT.
For each model, please modify the train scripts with the chosen datasets: dataset
is set to one of the three public datasets {flchain, support, seer}
, the default is support
.
simple=True
(default), DATE is chosen. Otherwise, modify in train_date.py.) python train_date.py
python train_draft.py
Once the networks are trained and the results are saved, we extract the following key results: