Demo Data from EDBT 2026 / reviewers in the wild / expert
Chengping Rao
dblp:259/1432
· DBLP profile ↗
1ranked-venue papers
1as 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 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 |
Deep learning architectures and training · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 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
physics-informed neural network |
0.6 | 1 | 2022 | Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning · ICLR 2022 |
Computational science and engineering › partial differential equations
partial differential equation discovery |
0.6 | 1 | 2022 | Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning · ICLR 2022 |
Methods — techniques the papers use, named apart from their topics
sparse data · 1.1physics-encoded learning · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Chengping Rao, Pu Ren, Yang Liu 0130, Hao Sun 0002 |
ICLR | 1 |