Diagrammatic Summaries for Neural ArchitecturesCitation formats

Standard

Diagrammatic Summaries for Neural Architectures. / Marshall, Guy; Jay, Caroline; Freitas, Andre.

International Conference on Learning Representations 2021. 2021.

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Harvard

Marshall, G, Jay, C & Freitas, A 2021, Diagrammatic Summaries for Neural Architectures. in International Conference on Learning Representations 2021.

APA

Marshall, G., Jay, C., & Freitas, A. (Accepted/In press). Diagrammatic Summaries for Neural Architectures. In International Conference on Learning Representations 2021

Vancouver

Marshall G, Jay C, Freitas A. Diagrammatic Summaries for Neural Architectures. In International Conference on Learning Representations 2021. 2021

Author

Marshall, Guy ; Jay, Caroline ; Freitas, Andre. / Diagrammatic Summaries for Neural Architectures. International Conference on Learning Representations 2021. 2021.

Bibtex

@inproceedings{61d0eff2ea7b46548803976a6cc974eb,
title = "Diagrammatic Summaries for Neural Architectures",
abstract = "This paper advocates for diagrammatic summary publications for machine learning system architecture papers. We review existing diagram-centric scholarly practices, and summarise relevant studies on neural network system architecture diagrams. We subsequently propose three opportunities: Diagram guidelines, diagrammatic system summary publications, and the community creation of a formal diagram standards, which could be integrated with existing LaTeX + PDF publication processes.",
author = "Guy Marshall and Caroline Jay and Andre Freitas",
year = "2021",
month = apr,
day = "7",
language = "English",
booktitle = "International Conference on Learning Representations 2021",

}

RIS

TY - GEN

T1 - Diagrammatic Summaries for Neural Architectures

AU - Marshall, Guy

AU - Jay, Caroline

AU - Freitas, Andre

PY - 2021/4/7

Y1 - 2021/4/7

N2 - This paper advocates for diagrammatic summary publications for machine learning system architecture papers. We review existing diagram-centric scholarly practices, and summarise relevant studies on neural network system architecture diagrams. We subsequently propose three opportunities: Diagram guidelines, diagrammatic system summary publications, and the community creation of a formal diagram standards, which could be integrated with existing LaTeX + PDF publication processes.

AB - This paper advocates for diagrammatic summary publications for machine learning system architecture papers. We review existing diagram-centric scholarly practices, and summarise relevant studies on neural network system architecture diagrams. We subsequently propose three opportunities: Diagram guidelines, diagrammatic system summary publications, and the community creation of a formal diagram standards, which could be integrated with existing LaTeX + PDF publication processes.

M3 - Conference contribution

BT - International Conference on Learning Representations 2021

ER -