Demo Data from VLDB 2026 / reviewers in the wild / expert
Hannah M. Schlüter
dblp:303/0319
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-5965-7889ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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 |
Time series and sequential data · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Time series and sequential data
anomaly detection |
0.6 | 1 | 2022 | Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization · ECCV (31) 2022 |
Machine learning › Time series and sequential data › anomaly detection
self-supervised anomaly detection |
0.6 | 1 | 2022 | Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization · ECCV (31) 2022 |
Methods — techniques the papers use, named apart from their topics
synthetic anomalies · 0.6self-supervised learning · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization
Hannah M. Schlüter, Jeremy Tan, Benjamin Hou, Bernhard Kainz |
ECCV (31) | 1 |