Multiscale, Nonlinear and Adaptive Approximation II

Edited by Ronald DeVore () and Angela Kunoth ()

in Springer Books from Springer

Date: 2024
ISBN: 978-3-031-75802-7
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Chapters in this book:

Prologue to Multiscale, Nonlinear and Adaptive Approximation II

Ronald A. DeVore and Angela Kunoth

Introduction: Wolfgang Dahmen’s mathematical work (as of 2009)

Ronald A. DeVore and Angela Kunoth

Multilevel Representations of Random Fields and Sparse Approximations of Solutions to Random PDEs

Markus Bachmayr and Albert Cohen

Nonlinear compressive reduced basis approximation for multi-parameter elliptic problem

Hassan Ballout, Yvon Maday and Christophe Prud’homme

Sparse Besov Space Analysis of Representations in Machine Learning

Ido Ben Shaul and Shai Dekel

Joint Denoising and Line Distortion Correction for Raster-Scanned Image Series

Benjamin Berkels and Peter Binev

The Approximation of Cauchy-Stieltjes and Laplace-Stieltjes Functions

Dietrich Braess and Wolfgang Hackbusch

Approximating Partial Differential Equations without Boundary Conditions

Andrea Bonito and Diane Guignard

Constructions of Bounded Solutions of $$ \textit{di}\upsilon $$ u = f in Critical Spaces

Albert Cohen, Ronald DeVore and Eitan Tadmor

On the importance of the $$ \varepsilon $$ -regularization of the distribution-dependent Mumford–Shah model for hyperspectral image segmentation

Jan-Christopher Cohrs and Benjamin Berkels

A Note on Best n-term Approximation for Generalized Wiener Classes

Ronald DeVore, Guergana Petrova and Przemysław Wojtaszczyk

Stable Truncation and Root-Independent Normalization of Tree Tensor Networks

Lars Grasedyck, Sebastian Krämer and Dieter Moser

Tree-Based Nonlinear Reduced Modeling

Diane Guignard and Olga Mula

Samplets: Wavelet Concepts for Scattered Data

Helmut Harbrecht and Michael Multerer

A novel multilevel approach for the efficient computation of random hyperbolic conservation laws

Michael Herty, Adrian Kolb and Siegfried Müller

On the Construction of Bases and Frames with Applications

Kamen G. Ivanov, Gerard Kerkyacharian, George Kyriazis and Pencho Petrushev

Towards Continuous Mathematical Models for the Analysis of Classes of Deep Neural Networks

Angela Kunoth, Mathias Oster and Reinhold Schneider

Unstoppable Mathematicians

Dominique Picard

Some Thoughts on Compositional Tensor Networks

Reinhold Schneider and Mathias Oster

Efficient least squares discretizations for Unique Continuation and Cauchy problems

Rob Stevenson

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DOI: 10.1007/978-3-031-75802-7

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