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Ronald A. DeVore and Angela Kunoth, Prologue to Multiscale, Nonlinear and Adaptive Approximation II -- Ronald A. DeVore and Angela Kunoth, Introduction: Wolfgang Dahmen's mathematical work (as of 2009) -- Markus Bachmayr and Albert Cohen, Multilevel Representations of Random Fields and Sparse Approximations of Solutions to Random PDEs -- Hassan Ballout and Yvon Maday and Christophe Prud'homme, Nonlinear compressive reduced basis approximation for multi-parameter elliptic problem -- Ido Ben Shaul and Shai Dekel, Sparse Besov Space Analysis of Representations in Machine Learning -- Benjamin Berkels and Peter Binev, Joint Denoising and Line Distortion Correction for Raster-Scanned Image Series -- Dietrich Braess and Wolfgang Hackbusch, The Approximation of Cauchy-Stieltjes and Laplace-Stieltjes Functions -- Andrea Bonito and Diane Guignard, Approximating Partial Differential Equations without Boundary Conditions -- Albert Cohen and Ronald DeVore and Eitan Tadmor, Constructions of Bounded Solutions of div u= f in Critical Spaces -- Jan-Christopher Cohrs and Benjamin Berkels, On the importance of the ε-regularization of the distribution-dependent Mumford-Shah model for hyperspectral image segmentation -- Ronald DeVore, Guergana Petrova and Przemysław Wojtaszczyk, A Note on Best n-term Approximation for Generalized Wiener Classes -- Lars Grasedyck, Sebastian Krämer and Dieter Moser, Stable Truncation and Root-Independent Normalization of Tree Tensor Networks -- Diane Guignard and Olga Mula, Tree-Based Nonlinear Reduced Modeling -- Helmut Harbrecht and Michael Multerer, Samplets: Wavelet Concepts for Scattered Data -- Michael Herty, Adrian Kolb, and Siegfried Müller, A novel multilevel approach for the efficient computation of random hyperbolic conservation laws -- Kamen G. Ivanov, Gerard Kerkyacharian, George Kyriazis, and Pencho Petrushev, On the Construction of Bases and Frames with Applications -- Angela Kunoth and Mathias Oster and Reinhold Schneider, Towards a Continuous Mathematical Model for the Analysis of Classes of Deep Neural Networks -- Dominique Picard, Unstoppable Mathematicians -- Reinhold Schneider and Mathias Oster, Some Thoughts on Compositional Tensor Networks -- Rob Stevenson, Efficient least squares discretizations for Unique Continuation and Cauchy problems. |