Demo Data from EDBT 2026 / reviewers in the wild / expert
Xiaopei Yang
dblp:364/2956
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 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
2 papers |
Generative modeling · 50% Representation and self-supervised learning · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Representation and self-supervised learning › representation learning
disentangled representation learning |
0.9 | 1 | 2025 | SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models · ICCV 2025 |
Machine learning › Generative modeling
normalizing flow |
0.9 | 1 | 2025 | SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models · ICCV 2025 |
Machine learning › Generative modeling › generative model › continuous-time generative model
stochastic interpolants |
0.9 | 1 | 2025 | Stochastic Interpolants for Revealing Stylistic Flows Across the History of Art · ICCV 2025 |
Machine learning › Representation and self-supervised learning › representation learning › disentangled representation learning
style-content disentanglement |
0.9 | 1 | 2025 | SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models · ICCV 2025 |
Methods — techniques the papers use, named apart from their topics
stochastic interpolants · 1.7generative modeling · 1.7flow model · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Stochastic Interpolants for Revealing Stylistic Flows Across the History of Art
Pingchuan Ma 0006, Ming Gui, Johannes Schusterbauer, Xiaopei Yang, Olga Grebenkova, Vincent Tao Hu, Björn Ommer |
ICCV | 4 |
| 2025 | SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models
Pingchuan Ma 0006, Xiaopei Yang, Yusong Li, Ming Gui, Felix Krause 0002, Johannes Schusterbauer, Björn Ommer |
ICCV | 2 |