ANIMATE: Unsupervised Attributed Graph Anomaly Detection with Masked Graph Transformers

Jingtao Hu, Yi Zhang, Chengzhang Zhu, Changsheng Hou

Open source

DOI: 10.3390/s26103176
Published: 2026-05-17
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26103176,
  title = {ANIMATE: Unsupervised Attributed Graph Anomaly Detection with Masked Graph Transformers},
  author = {Jingtao Hu and Yi Zhang and Chengzhang Zhu and Changsheng Hou},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26103176},
  url = {https://doi.org/10.3390/s26103176}
}

RIS

TY  - JOUR
TI  - ANIMATE: Unsupervised Attributed Graph Anomaly Detection with Masked Graph Transformers
AU  - Jingtao Hu
AU  - Yi Zhang
AU  - Chengzhang Zhu
AU  - Changsheng Hou
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26103176
UR  - https://doi.org/10.3390/s26103176
ER  -

APA

Hu, J., Zhang, Y., Zhu, C., & Hou, C. (2026). ANIMATE: Unsupervised Attributed Graph Anomaly Detection with Masked Graph Transformers. Sensors. https://doi.org/10.3390/s26103176

Source records

crossref · retrieved 2026-11-08T12:43:39.008Z