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De Gruyter Data-driven Models in Inverse Problems Book

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Description

Explore the paradigm shift in applied mathematics with Data-driven Models in Inverse Problems: 31. Part of the Radon Series on Computational and Applied Mathematics, this volume examines how learning-based methods are transforming the field of inverse problems. This research volume brings together experts from the inverse problem community to demonstrate how to combine model-driven and data-driven approaches. Readers will gain insight into both practical applications and theoretical issues within this cutting-edge area of study. It is an essential resource for understanding how data-driven methods are revolutionizing modern mathematical research.

Key Features

This book is part of the Radon Series on Computational and Applied Mathematics, volume 31.

Published by De Gruyter, this volume focuses on the revolution of learning-based methods in applied mathematics.

The content covers the shift toward data-driven approaches within the field of inverse problems.

Contributors from the inverse problem community provide insights into combining model- and data-driven methods.

The text addresses both theoretical issues and practical applications in computational mathematics.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
18 November 2024
Listed Since
09 July 2024

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