Data-Driven Models in Inverse Problems - (Radon Computational and Applied Mathematics) by Tatiana A Bubba (Hardcover)
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About this item
Highlights
- Advances in learning-based methods are revolutionizing several fields in applied mathematics, including inverse problems, resulting in a major paradigm shift towards data-driven approaches.
- About the Author: long Bio (mandatory for Amazon Top Titles)
- 508 Pages
- Mathematics, Applied
- Series Name: Radon Computational and Applied Mathematics
Description
About the Book
Advances in learning-based methods are revolutionizing several fields in applied mathematics, including inverse problems, resulting in a major paradigm shift towards data-driven approaches. This volume, which is inspired by this cutting-edge area ofBook Synopsis
Advances in learning-based methods are revolutionizing several fields in applied mathematics, including inverse problems, resulting in a major paradigm shift towards data-driven approaches. This volume, which is inspired by this cutting-edge area of research, brings together contributors from the inverse problem community and shows how to successfully combine model- and data-driven approaches to gain insight into practical and theoretical issues.
About the Author
long Bio (mandatory for Amazon Top Titles)Dimensions (Overall): 9.61 Inches (H) x 6.69 Inches (W) x 1.13 Inches (D)
Weight: 2.21 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 508
Genre: Mathematics
Sub-Genre: Applied
Series Title: Radon Computational and Applied Mathematics
Publisher: De Gruyter
Format: Hardcover
Author: Tatiana A Bubba
Language: English
Street Date: November 18, 2024
TCIN: 1003464653
UPC: 9783111250038
Item Number (DPCI): 247-02-1683
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 1.13 inches length x 6.69 inches width x 9.61 inches height
Estimated ship weight: 2.21 pounds
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