£175.54

Concepts and Techniques of Graph Neural Networks

AI & Machine Learning

Price data last checked 147 day(s) ago - refreshing...

View at Amazon

We'll watch every seller, every day. One email when your price arrives.

This is the usual price. Wait for it to drop, or tell us your number.

£176 today · usual range £0–£0 · best ever £164

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 584 days • 584 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 584 days • 8 price levels

Days at Price

Current Price

Price Analysis

Most common price: £198 (238 days, 40.8%)

Price range: £164 - £198

Price levels: 8 different prices over 584 days

Description

Recent advancements in graph neural networks have expanded their capacities and expressive power. Furthermore, practical applications have begun to emerge in a variety of fields including recommendation systems, fake news detection, traffic prediction, molecular structure in chemistry, antibacterial discovery physics simulations, and more. As a result, a boom of research at the juncture of graph theory and deep learning has revolutionized many areas of research. However, while graph neural networks have drawn a lot of attention, they still face many challenges when it comes to applying them to other domains, from a conceptual understanding of methodologies to scalability and interpretability in a real system. Concepts and Techniques of Graph Neural Networks provides a stepwise discussion, an exhaustive literature review, detailed analysis and discussion, rigorous experimentation results, and application-oriented approaches that are demonstrated with respect to applications of graph neural networks. The book also develops the understanding of concepts and techniques of graph neural networks and establishes the familiarity of different real applications in various domains for graph neural networks. Covering key topics such as graph data, social networks, deep learning, and graph clustering, this premier reference source is ideal for industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Product Specifications

Format: Paperback
ASIN: 1668469049
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 22 May 2023
Listed Since: 28 November 2022

Barcode

No barcode data available

Concepts and Techniques of Graph Neural Networks

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Concepts and Techniques of Graph Neural Networks

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

Graph Neural Networks: Foundations, Frontiers, and Applications

Advances in Graph Neural Networks (Synthesis Lectures on Data Mining and Knowledge Discovery)

Responsible Graph Neural Networks

Graph Neural Networks in Action

Deep Learning on Graphs

Graph Data Mining: Algorithm, Security and Application (Big Data Management)

Springer Graph Data Mining: Algorithm, Security and Application

Handbook of Research on Advanced Applications of Graph Theory in Modern Society (Advances in Computer and Electrical Engineering)

Hands-On Network Machine Learning with Python

Graph Algorithms: Practical Examples in Apache Spark and Neo4j

GRAPH THEORY NEW RESEARCH (Mathematics Research Developments)

Graph Machine Learning: Learn about the latest advancements in graph data to build robust machine learning models

Complex Networks & Their Applications IX: Volume 2, Proceedings of the Ninth International Conference on Complex Networks and Their Applications ... (Studies in Computational Intelligence, 944)

Graph-Powered Machine Learning

A Guide to Graph Algorithms

Knowledge Graphs and LLMs in Action

Graph Theory Applications (Universitext)

Knowledge Graphs: Fundamentals, Techniques, and Applications (Adaptive Computation and Machine Learning)

Graph Algorithms for Data Science: With Examples in Neo4j

Graph Theory: 244 (Graduate Texts in Mathematics, 244)

The Practitioner′s Guide to Graph Data: Applying Graph Thinking and Graph Technologies to Solve Complex Problems

Graph Algorithms And Applications 3: 06 (Journal of Graph Algorithms and Applications)