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SDE

Official code for the KDD 2025 paper:

SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting

Zixuan Weng, Jindong Han, Wenzhao Jiang, Hao Liu

Paper: https://arxiv.org/abs/2408.12068

Usage

  1. Install Pytorch and necessary dependencies.
pip install -r requirements.txt
  1. The datasets can be obtained from the iTransformer GitHub repository or downloaded directly from Google Drive.

  2. Train and evaluate the model:

# Multivariate forecasting with SDE
bash ./scripts/SAMBA/weather.sh

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Official Code for "SDE: A Simplified and Disentangled Dependency Encoding Framework for State Space Models in Time Series Forecasting" (KDD 2025)

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