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Graph Representation Learning(Synthesis Lectures on Artificial Intelligence and Machine Learning)

Format: Paperback

Condition: Standard Secondhand — £42.06
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This book is a foundational guide to graph representation learning, including state-of-the art advances, and introduces the highly successful graph neural network (GNN) formalism.

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.

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.

Genre: Computers, Artificial Intelligence
Format: Paperback
Published: 2020
Pages: 159
Publisher: Morgan & Claypool Publishers
ISBN: 9781681739632

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Our conditions mean the following:

  • New - a brand new book
  • Almost New - appears new but is actually secondhand.
  • Very Good - only minor imperfections such as minor scuffs to edge or cover or a price written in pencil or shop sticker.
  • Standard Secondhand - Clearly been read before, but not too bad. We do not recommend these for gifting. Spines usually creased. Could also include creases or folds to cover, some writing such as in the cover or elsewhere, underlining or highlighting, but might not do. Possibly some stains or marks. Similar in general to books in any secondhand shop or charity shop.
  • Poor Condition - Usually this will have a specific problem such as writing inside, water damage, missing dust jacket, heavy staining, large creases or cuts. These are readable copies but not nice ones. On other websites this condition is called 'Acceptable' or 'Fair' , but we want to be more honest.
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