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

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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".

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

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