EDBT 2026 Demo / reviewers in the wild / expert
Tzviel Frostig
dblp:289/4601
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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 |
Trustworthy machine learning · 50% Probabilistic and Bayesian machine learning · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Trustworthy machine learning
uncertainty and out-of-distribution detection |
0.6 | 1 | 2022 | A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks · ICLR 2022 |
Methods — techniques the papers use, named apart from their topics
statistical testing · 0.6deep neural network · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks
Matan Haroush, Tzviel Frostig, Ruth Heller, Daniel Soudry |
ICLR | 2 |
| 2020 | First Day of Life Prediction of Neonatal Intensive Care Unit Length of Stay
Alexis Mitelpunkt, Tzviel Frostig, Orli Kehat, Yoav Benjamini, Ahuva Weiss-Meilik |
AMIA | 2 |