Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting.

@inproceedings{liu-2023-spatiotemporal, author = {Hangchen Liu and Zheng Dong and Renhe Jiang and Jiewen Deng and Jinliang Deng and Quanjun Chen and Xuan Song}, editor = {Ingo Frommholz and Frank Hopfgartner and Mark Lee and Michael P. Oakes and Mounia Lalmas-Roelleke and Min Zhang and Rodrygo L. T. Santos}, title = {{Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting}}, booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}}, pages = {4125--4129}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3583780.3615160}, doi = {https://doi.org/10.1145/3583780.3615160} }