Diagrammatic Summaries for Neural Architectures

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


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.

Bibliographical metadata

Original languageEnglish
Title of host publicationInternational Conference on Learning Representations 2021
Publication statusAccepted/In press - 7 Apr 2021