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Multi-resolution Time-Series Transformer for Long-term Forecasting (MTST). arxiv

This paper has been accepted at AISTATS 2024.

Getting Started

  1. Install requirements. pip install -r requirements.txt

  2. Download data. You can download all the datasets from Autoformer. Create a seperate folder ./dataset and put all the csv files in the directory.

Multi-resolution Time Series Transformer (MTST)

  1. Training. All the scripts are in the directory ./scripts/MTST. For example,
sh ./scripts/MTST/etth2.sh

Acknowledgement

We appreciate the following github repo very much for the valuable code base and datasets:

https://github.com/yuqinie98/PatchTST

https://github.com/cure-lab/LTSF-Linear

https://github.com/zhouhaoyi/Informer2020

https://github.com/thuml/Autoformer

https://github.com/MAZiqing/FEDformer

https://github.com/alipay/Pyraformer

https://github.com/ts-kim/RevIN

https://github.com/timeseriesAI/tsai

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