Skip to content
Home/ Machine Learning Solutions for Inverse Problems: Part a: Volume 26
Machine Learning Solutions for Inverse Problems: Part a: Volume 26

Machine Learning Solutions for Inverse Problems: Part a: Volume 26

No customer reviews yet ISBN 9780443417894

Machine Learning Solutions for Inverse Problems: Part A, Volume 26 in the Handbook of Numerical Analysis, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Data-Driven Approaches for Generalized Lasso Problems, Implicit Regularization of the Deep Inverse Prior via (Inertial) Gradient Flow, Generalized Hardness of Approximation, Hallucinations, and Trustworthiness in Machine Learning for Inverse Problems, Energy-Based Models for Inverse Imaging Problems, Regularization Theory of Stochastic Iterative Methods for Solving Inverse Problems, and more.

Other sections cover Advances in Identifying Differential Equations from Noisy Data Observations, The Complete Electrode Model for Electrical Impedance Tomography: A Comparative Study of Deep Learning and Analytical Methods, Learned Iterative Schemes: Neural Network Architectures for Operator Learning, Jacobian-Free Backpropagation for Unfolded Schemes with Convergence Guarantees, and Operator Learning Meets Inverse Problems: A Probabilistic Perspective

About the author

Product details

Pub dateOct 28, 2025
ISBN-10044341789X
ISBN-139780443417894
LanguageEnglish
Last updated 2025-11-05 22:37
$265.95
In stock — ships in 24 hours with free tracking
Delivery by Monday, September 14, 2026
Qty
Sign in to Add to Saved list
Free delivery on orders over $35.
15-day returns. Any reason.
Secure checkout. We never store card details.

Readers who bought this also bought

More from Mathematical Analysis
See all
Mathematics: MacMillan Science Library, 4 Volume Set
<p>This full-color update of the award-winning 2002 A-Z encyclopedia explains concepts, provides a historical overview, and explores careers in the field. Written for middle school/high school students, as well as non-math-major undergraduates, <em>Mathematics</em> contains some 300 entries that cover the basics of algebra, geometry and trigonometry, with the goal of making these topics more accessible and interesting. Readers will see the uses and effects of math in daily life, while short biographies highlight notable mathematicians. Thirty percent of the content is new to this edition, highlighting advances in mathematics since 2000. <em>Mathematics</em> is illustrated with images, equations, tables, and figures, and includes sidebars.<br /><br />Both the original edition and the new were shaped by expert boards who determined the entry list and reviewed content. Each entry contains a bibliography/suggestions for further reading and crossâ references directing the users to articles of related interest.<br />
$1,251.17
Problems in Real Analysis (Revised)
Aliprantis, Charalambos D
$122.73
Principles of Real Analysis (Revised)
Aliprantis, Charalambos D
$173.55
Probability & Measure Theory
Ash, Robert B
$149.30
Working Analysis
Cooper, Jeffery
$155.07
Regression Analysis
Ping Sa
$47.60