£156.68

World Scientific Publishing Company World Scientific Equivariant and Coordinate Independent CNNs

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Description

Explore the intersection of advanced physics and machine learning with Equivariant and Coordinate Independent Convolutional Networks: A Gauge Field Theory of Neural Networks. Published by World Scientific Publishing Company, this volume is part of the Progress In Data Science series, providing a deep look into the mathematical frameworks that define modern AI architectures. This book addresses the fundamental principles of gauge field theory as applied to neural networks. It is designed for professionals and researchers working within the fields of computer science, artificial intelligence, and machine learning. By bridging the gap between theoretical physics and computational models, this text offers a unique perspective on how coordinate independence and equivariance impact the performance and structure of convolutional networks. Whether you are studying advanced data science or researching the mathematical foundations of deep learning, this publication serves as a specialized resource for understanding complex network behaviors. It is an essential addition to any technical library focused on the evolving landscape of AI and machine learning research.

Key Features

Part of the Progress In Data Science series for specialized academic study.

Published by World Scientific Publishing Company to ensure high research standards.

Focuses on the application of gauge field theory within neural network design.

Targets advanced topics in AI and machine learning for technical professionals.

Provides a deep mathematical look at coordinate independent convolutional networks.

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
24 December 2025
Listed Since
07 December 2024

Barcode

No barcode data available

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