Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020.

Xu Z, Wei L, Zhao H, Ying R, Yao Q, Tu WW, Guyon I

DOI: 10.3389/frai.2022.905104
Published: 2022
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2022.905104,
  title = {Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020.},
  author = {Xu Z and Wei L and Zhao H and Ying R and Yao Q and Tu WW and Guyon I},
  year = {2022},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2022.905104},
  url = {https://doi.org/10.3389/frai.2022.905104}
}

RIS

TY  - JOUR
TI  - Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020.
AU  - Xu Z
AU  - Wei L
AU  - Zhao H
AU  - Ying R
AU  - Yao Q
AU  - Tu WW
AU  - Guyon I
PY  - 2022
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2022.905104
UR  - https://doi.org/10.3389/frai.2022.905104
ER  -

APA

Z, X., L, W., H, Z., R, Y., Q, Y., WW, T., & I, G. (2022). Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2022.905104

Source records

pubmed · retrieved 2026-09-25T21:44:07.394Z