Graph learning· 2013
Spectral Networks and Locally Connected Networks on Graphs
On the reading lists
- #255 in the Top 500 (2026 edition)
- #13 in Graph learning (2026 edition)
Why it matters
Pioneered spectral convolutional architectures for irregular graph domains.
Condensed from the expert lists' notes.
The record
- First released
- 2013 (from arXiv 1312.6203)
- Published
- 2014
- Citations
- 5,527 citations, as counted by
Semantic Scholar (non-commercial licence) - Named by
- both expert lists
- Score
- 0.480 · computed rank 255 · consensus 0.84, must-read 0, citations percentile 0.652 (2010s · graphs), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0), and
Semantic Scholar (used under its non-commercial API licence). Each count names its source. See the method.