Author: I. M. Gelfand Publisher: Courier Corporation ISBN: 0486425649 Category : Mathematics Languages : en Pages : 116
Book Description
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: William L. William L. Hamilton Publisher: Springer Nature ISBN: 3031015886 Category : Computers Languages : en Pages : 141
Book Description
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.
Author: László Lovász Publisher: American Mathematical Soc. ISBN: 1470450879 Category : Geometry Languages : en Pages : 444
Book Description
Graphs are usually represented as geometric objects drawn in the plane, consisting of nodes and curves connecting them. The main message of this book is that such a representation is not merely a way to visualize the graph, but an important mathematical tool. It is obvious that this geometry is crucial in engineering, for example, if you want to understand rigidity of frameworks and mobility of mechanisms. But even if there is no geometry directly connected to the graph-theoretic problem, a well-chosen geometric embedding has mathematical meaning and applications in proofs and algorithms. This book surveys a number of such connections between graph theory and geometry: among others, rubber band representations, coin representations, orthogonal representations, and discrete analytic functions. Applications are given in information theory, statistical physics, graph algorithms and quantum physics. The book is based on courses and lectures that the author has given over the last few decades and offers readers with some knowledge of graph theory, linear algebra, and probability a thorough introduction to this exciting new area with a large collection of illuminating examples and exercises.
Author: Naomi B. Robbins Publisher: Wiley-Interscience ISBN: Category : Business & Economics Languages : en Pages : 432
Book Description
A succinct and highly readable guide to creating effective graphs The right graph can be a powerful tool for communicating information, improving a presentation, or conveying your point in print. If your professional endeavors call for you to present data graphically, here's a book that can help you do it more effectively. Creating More Effective Graphs gives you the basic knowledge and techniques required to choose and create appropriate graphs for a broad range of applications. Using real-world examples everyone can relate to, the author draws on her years of experience in graphical data analysis and presentation to highlight some of today's most effective methods. In clear, concise language, the author answers such common questions as: What constitutes an effective graph for communicating data? How do I choose the type of graph that is best for my data? How do I recognize a misleading graph? Why do some graphs have logarithmic scales? In no time you'll graduate from bar graphs and pie charts to graphs that illuminate data like: Dot plots Box plots Scatterplots Linked micromaps Trellis displays Mosaic plots Month plots Scatterplot matrices . . . most of them requiring only inexpensive, easily downloadable software. Whether you're a novice at graphing or already use graphs in your work but want to improve them, Creating More Effective Graphs will help you develop the kind of clear, accurate, and well-designed graphs that will allow your data to be understood.
Author: Gregory Berkolaiko Publisher: American Mathematical Soc. ISBN: 0821892118 Category : Mathematics Languages : en Pages : 291
Book Description
A ``quantum graph'' is a graph considered as a one-dimensional complex and equipped with a differential operator (``Hamiltonian''). Quantum graphs arise naturally as simplified models in mathematics, physics, chemistry, and engineering when one considers propagation of waves of various nature through a quasi-one-dimensional (e.g., ``meso-'' or ``nano-scale'') system that looks like a thin neighborhood of a graph. Works that currently would be classified as discussing quantum graphs have been appearing since at least the 1930s, and since then, quantum graphs techniques have been applied successfully in various areas of mathematical physics, mathematics in general and its applications. One can mention, for instance, dynamical systems theory, control theory, quantum chaos, Anderson localization, microelectronics, photonic crystals, physical chemistry, nano-sciences, superconductivity theory, etc. Quantum graphs present many non-trivial mathematical challenges, which makes them dear to a mathematician's heart. Work on quantum graphs has brought together tools and intuition coming from graph theory, combinatorics, mathematical physics, PDEs, and spectral theory. This book provides a comprehensive introduction to the topic, collecting the main notions and techniques. It also contains a survey of the current state of the quantum graph research and applications.
Author: Darran Stobbart Publisher: Maths Activity Books ISBN: 9781474960472 Category : Languages : en Pages : 0
Book Description
Discover all kinds of graphs and charts and how to use them in this entertaining activity book. The activities encourage children to collect and analyse data, from tallying the number of animals spotted on safari, to displaying types of weather on a bar chart and sorting animals into a Venn diagram. Quizzes after each section let children test what they've learned.
Author: Aidan Hogan Publisher: Morgan & Claypool Publishers ISBN: 1636392369 Category : Computers Languages : en Pages : 257
Book Description
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
Author: Bridget Heos Publisher: Math World ISBN: 9781622432356 Category : Juvenile Nonfiction Languages : en Pages : 0
Book Description
A class is learning a lesson on making graphs and interpreting data, and the class clown, Logan, has some off-the-wall answers to his classmates' surveys.
Author: I. M. Gelfand
Author: William L. William L. Hamilton
Author: László Lovász
Author: Naomi B. Robbins
Author: Gregory Berkolaiko
Author: Darran Stobbart
Author: Christine Taylor-Butler
Author: Aidan Hogan
Author: Bridget Heos
Author: Alan Frieze