Demo Data from VLDB 2026 / reviewers in the wild / expert
Jorge Pérez-Martín
dblp:201/2116
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-3588-7233ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1Applied, 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 |
Probabilistic and Bayesian machine learning · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Probabilistic and Bayesian machine learning › structured models › graphical models
bayesian network |
0.4 | 1 | 2019 | OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models · IJCAI 2019 |
Machine learning › Probabilistic and Bayesian machine learning › structured models
graphical models |
0.4 | 1 | 2019 | OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models · IJCAI 2019 |
Machine learning › Probabilistic and Bayesian machine learning › structured models › graphical models › directed graphical model
influence diagrams |
0.1 | 1 | 2019 | OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models · IJCAI 2019 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Cost-effectiveness analysis with unordered decisions
Francisco Javier Díez 0001, Manuel Luque, Manuel Arias 0004, Jorge Pérez-Martín |
Artif. Intell. Medicine | 4 |
| 2019 | OpenMarkov, an Open-Source Tool for Probabilistic Graphical ModelsabstractOpenMarkov is a Java open-source tool for creating and evaluating probabilistic graphical models, including Bayesian networks, influence diagrams, and some Markov models. With more than 100,000 lines of code, it offers some features for interactive learning, explanation of reasoning, and cost-effectiveness analysis, which are not available in any other tool. OpenMarkov has been used at universities, research centers, and large companies in more than 30 countries on four continents. Several models, some of them for real-world medical applications, built with OpenMarkov, are publicly available on Internet. Manuel Arias 0004, Jorge Pérez-Martín, Manuel Luque, Francisco Javier Díez 0001 |
IJCAI | 2 |
| 2017 | Advanced Algorithms for Medical Decision Analysis. Implementation in OpenMarkov
Manuel Arias 0004, Miguel Ángel Artaso, Iñigo Bermejo, Francisco Javier Díez 0001, Manuel Luque, Jorge Pérez-Martín |
AIME | 6 |