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Books in Numerical analysis

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    • Machine Learning Solutions for Inverse Problems: Part A

      • 1st Edition
      • Volume 26
      • October 14, 2025
      • English
      • Hardback
        9 7 8 0 4 4 3 4 1 7 8 9 4
      • eBook
        9 7 8 0 4 4 3 4 1 7 9 0 0
      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

    • Numerical Analysis meets Machine Learning

      • 1st Edition
      • Volume 25
      • June 13, 2024
      • English
      • Hardback
        9 7 8 0 4 4 3 2 3 9 8 4 7
      • eBook
        9 7 8 0 4 4 3 2 3 9 8 5 4
      Numerical Analysis Meets Machine Learning series, highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors.

    • Numerical Control: Part B

      • 1st Edition
      • Volume 24
      • February 20, 2023
      • Emmanuel Trélat + 1 more
      • English
      • Hardback
        9 7 8 0 3 2 3 8 5 0 6 0 5
      • eBook
        9 7 8 0 3 2 3 8 5 8 2 6 7
      Numerical Control: Part B, Volume 24 in the Handbook of Numerical Analysis series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this volume include Control problems in the coefficients and the domain for linear elliptic equations, Computational approaches for extremal geometric eigenvalue problems, Non-overlapping domain decomposition in space and time for PDE-constrained optimal control problems on networks, Feedback Control of Time-dependent Nonlinear PDEs with Applications in Fluid Dynamics, Stabilization of the Navier-Stokes equations - Theoretical and numerical aspects, Reconstruction algorithms based on Carleman estimates, and more. Other sections cover Discrete time formulations as time discretization strategies in data assimilation, Back and forth iterations/Time reversal methods, Unbalanced Optimal Transport: from Theory to Numerics, An ADMM Approach to the Exact and Approximate Controllability of Parabolic Equations, Nonlocal balance laws -- an overview over recent results, Numerics and control of conservation laws, Numerical approaches for simulation and control of superconducting quantum circuits, and much more.

    • Numerical Control: Part A

      • 1st Edition
      • Volume 23
      • February 15, 2022
      • English
      • Hardback
        9 7 8 0 3 2 3 8 5 0 5 9 9
      • eBook
        9 7 8 0 3 2 3 8 5 3 3 9 2
      Numerical Control: Part A, Volume 23 in the Handbook of Numerical Analysis series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this volume include Numerics for finite-dimensional control systems, Moments and convex optimization for analysis and control of nonlinear PDEs, The turnpike property in optimal control, Structure-Preserving Numerical Schemes for Hamiltonian Dynamics, Optimal Control of PDEs and FE-Approximation, Filtration techniques for the uniform controllability of semi-discrete hyperbolic equations, Numerical controllability properties of fractional partial differential equations, Optimal Control, Numerics, and Applications of Fractional PDEs, and much more.

    • Geometric Partial Differential Equations - Part 2

      • 1st Edition
      • Volume 22
      • January 26, 2021
      • Andrea Bonito + 1 more
      • English
      • Hardback
        9 7 8 0 4 4 4 6 4 3 0 5 6
      • eBook
        9 7 8 0 4 4 4 6 4 3 0 6 3
      Besides their intrinsic mathematical interest, geometric partial differential equations (PDEs) are ubiquitous in many scientific, engineering and industrial applications. They represent an intellectual challenge and have received a great deal of attention recently. The purpose of this volume is to provide a missing reference consisting of self-contained and comprehensive presentations. It includes basic ideas, analysis and applications of state-of-the-art fundamental algorithms for the approximation of geometric PDEs together with their impacts in a variety of fields within mathematics, science, and engineering.

    • Geometric Partial Differential Equations - Part I

      • 1st Edition
      • Volume 21
      • January 14, 2020
      • English
      • Hardback
        9 7 8 0 4 4 4 6 4 0 0 3 1
      • eBook
        9 7 8 0 4 4 4 6 4 0 0 4 8
      Besides their intrinsic mathematical interest, geometric partial differential equations (PDEs) are ubiquitous in many scientific, engineering and industrial applications. They represent an intellectual challenge and have received a great deal of attention recently. The purpose of this volume is to provide a missing reference consisting of self-contained and comprehensive presentations. It includes basic ideas, analysis and applications of state-of-the-art fundamental algorithms for the approximation of geometric PDEs together with their impacts in a variety of fields within mathematics, science, and engineering.

    • Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2

      • 1st Edition
      • Volume 20
      • October 15, 2019
      • English
      • Hardback
        9 7 8 0 4 4 4 6 4 1 4 0 3
      • eBook
        9 7 8 0 4 4 4 6 4 1 4 1 0
      Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20, surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more.

    • Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 1

      • 1st Edition
      • Volume 19
      • November 8, 2018
      • English
      • Hardback
        9 7 8 0 4 4 4 6 4 2 0 5 9
      • eBook
        9 7 8 0 4 4 4 6 4 2 0 6 6
      Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion.

    • A Contemporary Study of Iterative Methods

      • 1st Edition
      • February 13, 2018
      • A. Alberto Magrenan + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 0 9 2 1 4 9
      • eBook
        9 7 8 0 1 2 8 0 9 4 9 3 8
      A Contemporary Study of Iterative Methods: Convergence, Dynamics and Applications evaluates and compares advances in iterative techniques, also discussing their numerous applications in applied mathematics, engineering, mathematical economics, mathematical biology and other applied sciences. It uses the popular iteration technique in generating the approximate solutions of complex nonlinear equations that is suitable for aiding in the solution of advanced problems in engineering, mathematical economics, mathematical biology and other applied sciences. Iteration methods are also applied for solving optimization problems. In such cases, the iteration sequences converge to an optimal solution of the problem at hand.

    • Handbook of Numerical Methods for Hyperbolic Problems

      • 1st Edition
      • Volume 18
      • January 16, 2017
      • Remi Abgrall + 1 more
      • English
      • Hardback
        9 7 8 0 4 4 4 6 3 9 1 0 3
      • eBook
        9 7 8 0 4 4 4 6 3 9 1 1 0
      Handbook on Numerical Methods for Hyperbolic Problems: Applied and Modern Issues details the large amount of literature in the design, analysis, and application of various numerical algorithms for solving hyperbolic equations that has been produced in the last several decades. This volume provides concise summaries from experts in different types of algorithms, so that readers can find a variety of algorithms under different situations and become familiar with their relative advantages and limitations.