DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability

Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi. DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. In Shashi Shekhar, Zhi-Hua Zhou, Yao-Yi Chiang, Gregor Stiglic, editors, Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023. pages 442-450, SIAM, 2023. [doi]

@inproceedings{CongWTGXCM23,
  title = {DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability},
  author = {Weilin Cong and Yanhong Wu and Yuandong Tian and Mengting Gu and Yinglong Xia and Chun-cheng Jason Chen and Mehrdad Mahdavi},
  year = {2023},
  doi = {10.1137/1.9781611977653.ch50},
  url = {https://doi.org/10.1137/1.9781611977653.ch50},
  researchr = {https://researchr.org/publication/CongWTGXCM23},
  cites = {0},
  citedby = {0},
  pages = {442-450},
  booktitle = {Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023},
  editor = {Shashi Shekhar and Zhi-Hua Zhou and Yao-Yi Chiang and Gregor Stiglic},
  publisher = {SIAM},
  isbn = {978-1-61197-765-3},
}