Demo Data from EDBT 2026 / reviewers in the wild / expert
Michael Leyton
dblp:88/4277
· DBLP profile ↗
10ranked-venue papers
8as first author
0since 2021 · last 2004
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 8 · 6 first-authorArtificial intelligence and machine learning · 4 · 3 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author
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 |
Knowledge representation and reasoning · 100% | |
| Computer graphics and multimedia
1 paper |
Geometric modeling and processing · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Operating systems · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
qualitative reasoning |
0.0 | 1 | 1989 | Processes at Discontinuities · IJCAI 1989 |
Geometric modeling and processing › procedural modeling
shape grammar |
0.0 | 1 | 1988 | A Process-Grammar for Shape · Artif. Intell. 1988 |
Operating systems › resource management › process management
process recovery |
0.0 | 1 | 1987 | Process Recovery · IJCAI 1987 |
Methods — techniques the papers use, named apart from their topics
process grammar · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | A Generative Theory of ShapeabstractThis talk gives an introduction to my book, A Generative Theory of Shape (Springer-Verlag, 550pages). The purpose of the book is to develop a generative theory of shape that has two properties regarded as fundamental to intelligence - maximizing transfer of structure and maximizing recoverability of the generative operations. These two properties are particularly important in the representation of complex shape - which is the main concern of the book. The primary goal of the theory is the conversion of complexity into understandability. For this purpose, a mathematical theory is presented of how understandability is created in a structure. This is achieved by developing a group-theoretic approach to formalizing transfer and recoverability. To handle complex shape, a new class of groups is developed, called unfolding groups. These unfold structure from a maximally collapsed version of that structure. A principal aspect of the theory is that it develops a group-theoretic formalization of major object-oriented concepts such as inheritance. The result is an object-oriented theory of geometry. Michael Leyton |
SMI | 1 |
| 1990 | 3D symmetry-curvature duality theorems
Alan L. Yuille, Michael Leyton |
Comput. Vis. Graph. Image Process. | 2 |
| 1989 | Processes at Discontinuities
Patrick J. Hayes, Michael Leyton |
IJCAI | 2 |
| 1988 | A Process-Grammar for Shape
Michael Leyton |
Artif. Intell. | 1 |
| 1987 | Process Recovery
Michael Leyton |
IJCAI | 1 |
| 1987 | Nested structures of control: An intuitive view
Michael Leyton |
Comput. Vis. Graph. Image Process. | 1 |
| 1987 | Symmetry-curvature duality
Michael Leyton |
Comput. Vis. Graph. Image Process. | 1 |
| 1986 | Constraint-Theorems on the Prototypification of Shape
Michael Leyton |
AAAI | 1 |
| 1986 | Principles of information structure common to six levels of the human cognitive system
Michael Leyton |
Inf. Sci. | 1 |
| 1985 | Generative systems of analyzers
Michael Leyton |
Comput. Vis. Graph. Image Process. | 1 |