EDBT 2026 Demo / reviewers in the wild / expert
Mayeul d'Avezac
dblp:80/10871
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021
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 · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Deep learning architectures and training
equivariant neural network |
0.5 | 1 | 2021 | Efficient Generalized Spherical CNNs · ICLR 2021 |
Machine learning › Deep learning architectures and training › equivariant neural network
spherical CNN |
0.5 | 1 | 2021 | Efficient Generalized Spherical CNNs · ICLR 2021 |
Methods — techniques the papers use, named apart from their topics
spherical convolution · 0.5group equivariance · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Efficient Generalized Spherical CNNs
Oliver J. Cobb, Christopher G. R. Wallis, Augustine N. Mavor-Parker, Augustin Marignier, Matthew A. Price, Mayeul d'Avezac, Jason D. McEwen |
ICLR | 6 |