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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.
FOREWORD BY GUY KAWASAKI Presentation designer and internationally acclaimed communications expert Garr Reynolds, creator of the most popular Web site on presentation design and delivery on the Net — presentationzen.com — shares his experience in a provocative mix of illumination, inspiration, education, and guidance that will change the way you think about making presentations with PowerPoint or Keynote. Presentation Zen challenges the conventional wisdom of making "slide presentations" in today’s world and encourages you to think differently and more creatively about the preparation, design, and delivery of your presentations. Garr shares lessons and perspectives that draw upon practical advice from the fields of communication and business. Combining solid principles of design with the tenets of Zen simplicity, this book will help you along the path to simpler, more effective presentations.
New Methods of Geostatistical Analysis and Graphical Presentation
The new, updated edition of the successful book on interior design Interior Design Visual Presentation, Second Edition is fully revised to include the latest material on CAD, digital portfolios, resume preparation, and Web page design. It remains the only comprehensive guide to address the visual design and presentation needs of the interior designer, with coverage of design graphics, models, and presentation techniques in one complete volume. Approaches to the planning, layout, and design of interior spaces are presented through highly visual, step-by-step instructions, supplemented with more than forty pages of full-color illustrations, exercises at the end of each chapter, and dozens of new projects. With the serious designer in mind, it includes a diverse range of sample work, from student designers as well as well-known design firms such as Ellerbee and Beckett Architects and MS Architects.
Basic principles and technioques of chart design. Drafting techniques. Rectilinear coordinate charts. Bar and column charts. Semilogarithmic or ratio charts. Frequency graphs and related charts. Miscellaneous graphic forms. Statistical maps. Pictorial charts. Projection techniques in graphic presentation. Role of the computer in graphic presentation.