Skip to content

Implementation of "Neural Jump-Diffusion Temporal Point Processes" (ICML 2024 Spotlight)

Notifications You must be signed in to change notification settings

Zh-Shuai/NJDTPP

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Neural Jump-Diffusion Temporal Point Processes

The implementation of our ICML-2024 (Spotlight) paper "Neural Jump-Diffusion Temporal Point Processes".

Dataset

The real-world datasets are from "EasyTPP" and "NHP".

Installation

  1. Install the dependencies
conda env create -f environment.yml
  1. Activate the conda environment
conda activate NJDTPP
  1. Unzip the data
unzip data.zip

Reproducing the results from the paper

Go to the source directory:

cd experiments

This directory contains all experiments on three synthetic and six real-world datasets, for example:

  • Earthquake dataset
python earthquake.py

Citation

If you find this code useful, please consider citing our paper. Thanks!

@inproceedings{zhang2024neural,
  title={Neural Jump-Diffusion Temporal Point Processes},
  author={Zhang, Shuai and Zhou, Chuan and Liu, Yang and Zhang, Peng and Lin, Xixun and Ma, Zhi-Ming},
  booktitle={International Conference on Machine Learning},
  year={2024}
}

Acknowledgements and References

Parts of this code are based on and/or copied from the code of "NJSDE" and "SAHP".

About

Implementation of "Neural Jump-Diffusion Temporal Point Processes" (ICML 2024 Spotlight)

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages