Full length article: Compactly supported shearlets are optimally sparse
By Gitta Kutyniok, Wang-Q Lim. 2011
298 citations recorded by the source corpus.
Subfields: Applied Mathematics, Computational Mechanics, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/c38c8680e694e36babdb9496637d0e9d6dbfe59c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Applied Mathematics
- Thomas Pock
- Antonin Chambolle
- Wolfgang Hackbusch
- Hermann G. Matthies
- Felix Voigtländer
- Philipp Christian Petersen
- M. Espig
- Alexander Mielke
In Computational Mechanics
- Thomas Pock
- Antonin Chambolle
- Alexander Litvinenko
- M. Espig
- Wolfgang Hackbusch
- Hermann G. Matthies
- Elmar Zander
- Felix Voigtländer
In Computer Vision and Pattern Recognition
- Thomas Pock
- Antonin Chambolle
- Wolfgang Hackbusch
- Felix Voigtländer
- Philipp Christian Petersen
- M. Espig
- Luc Van Gool
- Lei Zhang
Citations in the corpus
- An introduction to continuous optimization for imaging (2016, methodology): “Let us show an example using the discrete shearlet transform, since it has been shown to provide optimal sparse approximations for cartoon-like images (Guo and Labate 2007, Easley, Labate and Lim 2008, Kutyniok and Lim 2011), for image inpainting.”
- Efficient Analysis of High Dimensional Data in Tensor Formats (2012, methodology): “with representation rank 231 was computed with the use of the stochastic Galerkin library [38].”
- Optimal approximation of piecewise smooth functions using deep ReLU neural networks (2017, background): “For instance, shearlets and curvelets provide optimal N -term approximation rates for piecewise C 2 ( R 2 ) functions with C 2 jump curves, [9, 29, 22, 39].”