Articoli correlati a Graph Representation Learning

Graph Representation Learning - Rilegato

 
9781681739656: Graph Representation Learning

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<p><b>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.</b></p> <p>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.</p> <p>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.</p>

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  • EditoreMorgan & Claypool
  • Data di pubblicazione2020
  • ISBN 10 1681739658
  • ISBN 13 9781681739656
  • RilegaturaCopertina rigida
  • LinguaInglese
  • Numero di pagine141
  • Contatto del produttorenon disponibile

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Altre edizioni note dello stesso titolo

9781681739632: Graph Representation Learning

Edizione in evidenza

ISBN 10:  1681739631 ISBN 13:  9781681739632
Casa editrice: Morgan & Claypool, 2020
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