Shearlets: Multiscale Analysis for Multivariate Data

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Solving inverse problems using data-driven models (2019, unknown): “…at 15:29:08, subject to the Cambridge Core terms of use, available at Finally, in applied harmonic analysis, `p-norms of wavelets have been proposed as regularizers (Daubechies et al. 1991, Mallat 2009, Unser and Blu 2000, Kutyniok and Labate 2012, Eldar and Kutyniok 2012, Foucart and Rauhut 2013).”
Compressed Sensing (2012, background): “Figure 3 illustrates a numerical result from [43] using wavelets (see [45]) and shearlets (see [42, 41]) as sparsifying frames.”
A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction (2015, background): “The past two decades have seen extensive research [23]–[32] devoted to developing structured transforms ada pted to a variety of features, most prominently, curvelet [28]–[30] and shearlet [31], [32] transforms, bot h f which are known to be very effective in extracting features characterized by cur”