This repository is the official implementation of the paper "Adjusting for Autocorrelated Errors in Neural Networks for Time Series" (arXiv link).

For simplicity, we only provide the code for time series forecasting. However, it is straightforward to implement our method with other models on other time series tasks as described in the appendix of the paper.

To install requirements:

pip3 install -r requirements.txt

Available datasets are located in the directory data/forecasting. Traffic is not included because it exceeds the 100MB size limit set by Github. However, you can download it here and format the it into a .npy file. ADI-related datasets are not released because they are proprietary.

To use your own dataset, format it into a numpy array with size TxN and saved it into the data directory as a .npy file.

Example commands can be found in run.sh.

@inproceedings{sun2021adjusting,
    title={Adjusting for Autocorrelated Errors in Neural Networks for Time Series Regression and Forecasting}, 
    author={Fan-Keng Sun and Christopher I. Lang and Duane S. Boning},
    booktitle = {Advances in Neural Information Processing Systems},
    year={2021},
}