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Demo Data from EDBT 2026 / reviewers in the wild / expert

Nadav Shamir

dblp:232/2992 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Deep learning architectures and training · 61% Graph learning · 30% Representation and self-supervised learning · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Deep learning architectures and training
equivariant neural network		 0.412019
Invariant and Equivariant Graph Networks · ICLR (Poster) 2019
Machine learning › Graph learning
graph neural network		 0.412019
Invariant and Equivariant Graph Networks · ICLR (Poster) 2019
Machine learning › Deep learning architectures and training › equivariant neural network
invariant network		 0.412019
Invariant and Equivariant Graph Networks · ICLR (Poster) 2019

Methods — techniques the papers use, named apart from their topics

equivariant message passing · 0.4
YearPublicationVenuePosition
2019 Invariant and Equivariant Graph Networks
Haggai Maron, Heli Ben-Hamu, Nadav Shamir, Yaron Lipman
 ICLR (Poster)3