Spectral-temporal dual view graph convolutional networks: A deep learning framework for dynamic bipartite graphs

Zhezhe Xing, Yuxin Ye, Ziheng Li, Jiawen Liu

Open source

DOI
10.1016/j.neunet.2026.109672
Published
2027-02
Container
Neural Networks
Publisher
Elsevier BV
Open access
unknown

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BibTeX

@article{allodium:10.1016/j.neunet.2026.109672,
  title = {Spectral-temporal dual view graph convolutional networks: A deep learning framework for dynamic bipartite graphs},
  author = {Zhezhe Xing and Yuxin Ye and Ziheng Li and Jiawen Liu},
  year = {2027},
  journal = {Neural Networks},
  doi = {10.1016/j.neunet.2026.109672},
  url = {https://doi.org/10.1016/j.neunet.2026.109672}
}

RIS

TY  - JOUR
TI  - Spectral-temporal dual view graph convolutional networks: A deep learning framework for dynamic bipartite graphs
AU  - Zhezhe Xing
AU  - Yuxin Ye
AU  - Ziheng Li
AU  - Jiawen Liu
PY  - 2027
JO  - Neural Networks
DO  - 10.1016/j.neunet.2026.109672
UR  - https://doi.org/10.1016/j.neunet.2026.109672
ER  - 

APA

Xing, Z., Ye, Y., Li, Z., & Liu, J. (2027). Spectral-temporal dual view graph convolutional networks: A deep learning framework for dynamic bipartite graphs. Neural Networks. https://doi.org/10.1016/j.neunet.2026.109672

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