Symmetry In Graphs
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Author | : Ted Dobson |
Publisher | : Cambridge University Press |
Total Pages | : 527 |
Release | : 2022-05-12 |
Genre | : Language Arts & Disciplines |
ISBN | : 1108429068 |
The first full-length book on the theme of symmetry in graphs, a fast-growing topic in algebraic graph theory.
Author | : Jose M. Rodriguez |
Publisher | : MDPI |
Total Pages | : 340 |
Release | : 2019-03-14 |
Genre | : Mathematics |
ISBN | : 303897658X |
This book contains the successful invited submissions to a Special Issue of Symmetry on the subject of “Graph Theory”. Although symmetry has always played an important role in Graph Theory, in recent years, this role has increased significantly in several branches of this field, including but not limited to Gromov hyperbolic graphs, the metric dimension of graphs, domination theory, and topological indices. This Special Issue includes contributions addressing new results on these topics, both from a theoretical and an applied point of view.
Author | : Gareth A. Jones |
Publisher | : Springer Nature |
Total Pages | : 239 |
Release | : 2020-01-10 |
Genre | : Mathematics |
ISBN | : 3030328082 |
This book consists of a selection of peer-reviewed contributions to the Workshop on Algebraic Graph Theory that took place in Pilsen, Czech Republic in October 2016. Primarily intended for early career researchers, it presents eight self-contained articles on a selection of topics within algebraic combinatorics, ranging from association schemes to symmetries of graphs and isomorphism testing. Algebraic combinatorics is a compelling mathematical discipline based on the powerful interplay of algebraic and combinatorial methods. Algebraic interpretation of combinatorial structures (such as symmetry or regularity) has often led to enlightening discoveries and powerful results, while discrete and combinatorial structures have given rise to new algebraic structures that have found valuable applications. In addition to these original research contributions, the reader will find a survey linking numerous threads in algebraic combinatorics, and an extensive tutorial showcasing the universality of algebraic methods in the study of combinatorial structures.
Author | : Andries E. Brouwer |
Publisher | : Springer Science & Business Media |
Total Pages | : 513 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 3642743412 |
Ever since the discovery of the five platonic solids in ancient times, the study of symmetry and regularity has been one of the most fascinating aspects of mathematics. Quite often the arithmetical regularity properties of an object imply its uniqueness and the existence of many symmetries. This interplay between regularity and symmetry properties of graphs is the theme of this book. Starting from very elementary regularity properties, the concept of a distance-regular graph arises naturally as a common setting for regular graphs which are extremal in one sense or another. Several other important regular combinatorial structures are then shown to be equivalent to special families of distance-regular graphs. Other subjects of more general interest, such as regularity and extremal properties in graphs, association schemes, representations of graphs in euclidean space, groups and geometries of Lie type, groups acting on graphs, and codes are covered independently. Many new results and proofs and more than 750 references increase the encyclopaedic value of this book.
Author | : Jenny A. Baglivo |
Publisher | : Cambridge University Press |
Total Pages | : 319 |
Release | : 1983-03-31 |
Genre | : Mathematics |
ISBN | : 9780521230438 |
The initial purposes of this 1983 text were to develop mathematical topics relevant to the study of the incidence and symmetry structures of geometrical objects and to expand the reader's geometric intuition. The two fundamental mathematical topics employed in this endeavor are graph theory and the theory of transformation groups. Part I, Incidence, starts with two sections on the basics of graph theory and continues with a variety of specific applications of graph theory. Following this, the text becomes more theoretical; here graph theory is used to study surfaces other than the plane and the sphere. Part II, Symmetry, starts with a section on rigid motions or symmetries of the plane, which is followed by another on the classification of planar patterns. Additionally, an overview of symmetry in three-dimensional space is provided, along with a reconciliation of graph theory and group theory in a study of enumeration problems in geometry.
Author | : Ian Stewart |
Publisher | : |
Total Pages | : 306 |
Release | : 2008-04-29 |
Genre | : Mathematics |
ISBN | : 0465082378 |
Author | : Gena Hahn |
Publisher | : Springer Science & Business Media |
Total Pages | : 456 |
Release | : 1997-06-30 |
Genre | : Mathematics |
ISBN | : 9780792346685 |
The last decade has seen two parallel developments, one in computer science, the other in mathematics, both dealing with the same kind of combinatorial structures: networks with strong symmetry properties or, in graph-theoretical language, vertex-transitive graphs, in particular their prototypical examples, Cayley graphs. In the design of large interconnection networks it was realised that many of the most fre quently used models for such networks are Cayley graphs of various well-known groups. This has spawned a considerable amount of activity in the study of the combinatorial properties of such graphs. A number of symposia and congresses (such as the bi-annual IWIN, starting in 1991) bear witness to the interest of the computer science community in this subject. On the mathematical side, and independently of any interest in applications, progress in group theory has made it possible to make a realistic attempt at a complete description of vertex-transitive graphs. The classification of the finite simple groups has played an important role in this respect.
Author | : I. M. Gelfand |
Publisher | : Courier Corporation |
Total Pages | : 116 |
Release | : 2002-01-01 |
Genre | : Mathematics |
ISBN | : 0486425649 |
This volume presents students with problems and exercises designed to illuminate the properties of functions and graphs. The 1st part of the book employs simple functions to analyze the fundamental methods of constructing graphs. The 2nd half deals with more complicated and refined questions concerning linear functions, quadratic trinomials, linear fractional functions, power functions, and rational functions. 1969 edition.
Author | : Lowell W. Beineke |
Publisher | : Cambridge University Press |
Total Pages | : 302 |
Release | : 2004-10-04 |
Genre | : Mathematics |
ISBN | : 9780521801973 |
There is no other book with such a wide scope of both areas of algebraic graph theory.
Author | : William L. William L. Hamilton |
Publisher | : Springer Nature |
Total Pages | : 141 |
Release | : 2022-06-01 |
Genre | : Computers |
ISBN | : 3031015886 |
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.