EDBT 2026 Demo / reviewers in the wild / expert
Matthew Choptuik
dblp:345/9588
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% | |
| Artificial intelligence
1 paper |
Deep learning architectures and training · 100% |
Topics — the 3 heaviest of 3, 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 |
0.7 | 1 | 2023 | A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks · ICLR 2023 |
Computational science and engineering › differential equations
initial value problem |
0.7 | 1 | 2023 | A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks · ICLR 2023 |
Computational science and engineering
partial differential equations |
0.7 | 1 | 2023 | A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks · ICLR 2023 |
Methods — techniques the papers use, named apart from their topics
neural network · 1.3PDE solver · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks
Marc Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson |
ICLR | 3 |