£160.00

Academic Press Machine Learning Solutions for Inverse Problems: Part B (Volume 27) (Handbook of Numerical Analysis, Volume 27)

Name: Machine Learning Solutions for Inverse Problems: Part B (Volume 27) (Handbook of Numerical Analysis, Volume 27)
Brand: Academic Press
Price: 160.0 GBP
Availability: InStock

Mathematical Analysis

It has never been this cheap. We have no record of a lower price.

£160 today · cheaper than every other day in the last 2 months

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 19 days • 19 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 19 days • 1 price levels

Days at Price

Price Analysis

Most common price: £160 (19 days, 100.0%)

Price range: £160 - £160

Price levels: 1 different prices over 19 days

Description

Machine Learning Solutions for Inverse Problems: Part B, Volume 27 in the Handbook of Numerical Analysis, continues the exploration of emerging approaches at the intersection of machine learning and inverse problem theory. This volume presents a collection of chapters addressing a wide range of contemporary topics, including deep image prior methods for computed tomography, data-consistent learning strategies, and unified frameworks for training and inversion in machine learning-based reconstruction methods. Additional chapters examine learned regularization techniques, generative models for inverse problems, and the integration of deep learning with traditional computational frameworks such as full waveform inversion and PDE-based inverse modeling. The volume also discusses advances in self-supervised learning, data selection strategies, plug-and-play denoising methods, and diffusion models for solving imaging inverse problems. Further contributions explore neural network representations, operator learning, and learned iterative schemes, along with theoretical perspectives on stability, approximation hardness, hallucinations, and trustworthiness in AI-driven inverse problem methodologies. Presents the latest developments in machine learning approaches for solving inverse problems Explores modern techniques, including deep learning, generative models, diffusion models, and operator learning Covers applications in imaging, tomography, and PDE-based inverse modeling Includes theoretical perspectives on stability, approximation hardness, and trustworthiness in AI for inverse problems Serves as a comprehensive reference for researchers in numerical analysis, computational mathematics, and scientific computing

Product Specifications

Brand: Academic Press
Format: hardcover
ASIN: 0443428174
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Mathematical Analysis
Domain: Amazon UK
Release Date: 05 October 2026
Listed Since: 11 March 2026

Barcode

No barcode data available

Academic Press Machine Learning Solutions for Inverse Problems: Part B (Volume 27) (Handbook of Numerical Analysis, Volume 27)

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Harmonic and Applied Analysis: From Radon Transforms to Machine Learning (Applied and Numerical Harmonic Analysis)

An Introduction to Capstone in Applied Analysis: A Fundamental Guide for Students and Instructors (Mathematics Research Developments)

Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications: 18 (Learning and Analytics in Intelligent Systems, 18)

Computed Radiation Imaging: Physics and Mathematics of Forward and Inverse Problems

Sampling, Wavelets, and Tomography (Applied and Numerical Harmonic Analysis)

Machine Learning and Image Interpretation (Advances in Computer Vision and Machine Intelligence)

Numerical Solution of Partial Differential Equations: Theory, Algorithms, and Their Applications: In Honor of Professor Raytcho Lazarov's 40 Years of ... Proceedings in Mathematics & Statistics, 45)

Spinal Imaging and Image Analysis: 18 (Lecture Notes in Computational Vision and Biomechanics, 18)

Handbook of Convex Optimization Methods in Imaging Science

AI and Machine Learning Paradigms for Health Monitoring System: Intelligent Data Analytics: 86 (Studies in Big Data, 86)

Boundary element methods for solving inverse problems: The modelling of contaminated fluid flows

An Introduction to Inverse Problems with Applications

Advanced Finite Element Methods with Applications: Selected Papers from the 30th Chemnitz Finite Element Symposium 2017: 128 (Lecture Notes in Computational Science and Engineering, 128)

Inverse Problems, Tomography, and Image Processing

Regularization of Inverse Problems: 375 (Mathematics and Its Applications, 375)

Integrating Artificial Intelligence with Virtual Screening: A New Era in Drug Discovery

Advanced Finite Element Methods with Applications: Selected Papers from the 30th Chemnitz Finite Element Symposium 2017: 128 (Lecture Notes in Computational Science and Engineering, 128)

Application of Machine Learning and Deep Learning Methods to Power System Problems

Applied Computer Vision and Soft Computing with Interpretable AI

Frontiers in PDE-Constrained Optimization: 163 (The IMA Volumes in Mathematics and its Applications, 163)

Nonlinear Least Squares for Inverse Problems: Theoretical Foundations and Step-by-Step Guide for Applications (Scientific Computation)

Techniques of Scientific Computing (Part 2) (Volume 5) (Handbook of Numerical Analysis, Volume 5)

Reshaping Geotechnical Engineering with Machine Learning: Theory, Applications, and Innovations

Parallel Scientific Computing and Optimization: Advances and Applications: 27 (Springer Optimization and Its Applications, 27)