Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting

@inproceedings{Liu2020BridgingTG,
  title={Bridging the Gap Between Training and Inference for Spatio-Temporal Forecasting},
  author={Hongbin Liu and Ickjai Lee},
  booktitle={ECAI},
  year={2020}
}
  • Hongbin Liu, Ickjai Lee
  • Published in ECAI 2020
  • Computer Science, Mathematics
  • Spatio-temporal sequence forecasting is one of the fundamental tasks in spatio-temporal data mining. It facilitates many real world applications such as precipitation nowcasting, citywide crowd flow prediction and air pollution forecasting. Recently, a few Seq2Seq based approaches have been proposed, but one of the drawbacks of Seq2Seq models is that, small errors can accumulate quickly along the generated sequence at the inference stage due to the different distributions of training and… CONTINUE READING
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