Demo Data from EDBT 2026 / reviewers in the wild / expert
Mark A. Peot
dblp:13/2414 · also Mark Alan Peot
· DBLP profile ↗
8ranked-venue papers
4as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 8 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-authorTheory of computation · 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
4 papers |
Knowledge representation and reasoning · 35% Planning, search and constraint satisfaction · 35% Probabilistic and Bayesian machine learning · 30% | |
| Databases, data mining, and information retrieval
1 paper |
Data models and query languages · 100% |
Topics — the 7 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data models and query languages
structured query |
0.0 | 1 | 2000 | A Compositional Structured Query Approach to Automated Inference · KR 2000 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › classical planning
partial-order planning |
0.0 | 2 | 1993 | Postponing Threats in Partial-Order Planning · AAAI 1993 Threat-Removal Strategies for Partial-Order Planning · AAAI 1993 |
Machine learning › Probabilistic and Bayesian machine learning › probabilistic inference
bayesian network inference |
0.0 | 1 | 1991 | Fusion and Propagation with Multiple Observations in Belief Networks · Artif. Intell. 1991 |
Machine learning › Probabilistic and Bayesian machine learning › probabilistic inference › approximate inference
belief propagation |
0.0 | 1 | 1991 | Fusion and Propagation with Multiple Observations in Belief Networks · Artif. Intell. 1991 |
Machine learning › Probabilistic and Bayesian machine learning › structured models
graphical models |
0.0 | 1 | 1991 | Fusion and Propagation with Multiple Observations in Belief Networks · Artif. Intell. 1991 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
plan generation |
0.0 | 1 | 1993 | Threat-Removal Strategies for Partial-Order Planning · AAAI 1993 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › search-based planning
plan-space planning |
0.0 | 1 | 1993 | Postponing Threats in Partial-Order Planning · AAAI 1993 |
Methods — techniques the papers use, named apart from their topics
partial-order planning · 0.0message passing · 0.0belief propagation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | A Compositional Structured Query Approach to Automated Inference
Yousri El Fattah, Mark A. Peot |
KR | 2 |
| 1998 | Learning From What You Don't Observe
Mark A. Peot, Ross D. Shachter |
UAI | 1 |
| 1996 | Geometric Implications of the Naive Bayes Assumption
Mark A. Peot |
UAI | 1 |
| 1993 | Threat-Removal Strategies for Partial-Order Planning
Mark A. Peot, David E. Smith 0001 |
AAAI | 1 |
| 1993 | Postponing Threats in Partial-Order Planning
David E. Smith 0001, Mark A. Peot |
AAAI | 2 |
| 1992 | Decision Making Using Probabilistic Inference Methods
Ross D. Shachter, Mark A. Peot |
UAI | 2 |
| 1991 | Fusion and Propagation with Multiple Observations in Belief Networks
Mark A. Peot, Ross D. Shachter |
Artif. Intell. | 1 |
| 1989 | Simulation Approaches to General Probabilistic Inference on Belief Networks
Ross D. Shachter, Mark A. Peot |
UAI | 2 |