S. Dekel

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Robust Recovery of Stream of Pulses using Convex Optimization pdf

Shai Dekel, Tamir Bendory, Arie Feuer, 2014, ArXiv.

Wavelet decompositions of Random Forests

S. Dekel, Iryna Nemirovsky, 2022 .

L G ] 7 M ay 2 01 8 Wavelet Decomposition of Gradient Boosting May 8 , 2018

S. Dekel, Oren Elisha, Ohad Morgan, 2018 .

A Mathematical Model for Adaptive Computed Tomography Sensing

Oren Barkan, Amir Averbuch, Shai Dekel, 2017, IEEE Transactions on Computational Imaging.

Anisotropic function spaces with applications

P. Petrushev, S. Dekel, 2009 .

Anisotropic Meshless Frames on ℝn

P. Petrushev, S. Dekel, Yongsheng Han, 2009 .

On dual spaces of anisotropic Hardy spaces

S. Dekel, Tal Weissblat, 2012 .

Two-Level-Split Decomposition of Anisotropic Besov Spaces

W. Dahmen, P. Petrushev, S. Dekel, 2010 .

Poly-scale refinability and subdivision

N. Dyn, S. Dekel, 2002 .

Wavelet Decompositions of Nonrefinable Shift Invariant Spaces

S. Dekel, D. Leviatan, 2002 .

Nearest Class-Center Simplification through Intermediate Layers

S. Dekel, Ido Ben-Shaul, 2022, TAG-ML.

Computational Harmonic Analysis Organizing Committee Conference Secretary General Information Lecture Theatres Foreign Currency Exchange Email/fax Sightseeing Trip Non-uniform Sampling and Reconstruction in Shift-invariant Spaces with Applications to Signal and Image Processing Multiwavelet Transfor

Say Song Goh, Ding-Xuan Zhou, W. Dahmen, 2022 .

Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions

S. Dekel, Tomer Galanti, Ido Ben-Shaul, 2023, ArXiv.

Wavelet Decomposition of Gradient Boosting

S. Dekel, Oren Elisha, Ohad Morgan, 2018, ArXiv.

Low Bit-Rate Image Coding Using Adaptive Geometric Piecewise Polynomial Approximation

Nira Dyn, Shai Dekel, Roman Kazinnik, 2007, IEEE Transactions on Image Processing.

Série des Documents de Travail n ° 2017-91 Hardy spaces associated with non-negative self-adjoint operators

P. Petrushev, G. Kerkyacharian, S. Dekel, 2018 .

Hardy spaces associated with non-negative self-adjoint operators

P. Petrushev, G. Kerkyacharian, S. Dekel, 2014, 1409.0424.

Whitney Estimates for Convex Domains with Applications to Multivariate Piecewise Polynomial Approximation

Shai Dekel, Dany Leviatan, S. Dekel, 2004, Found. Comput. Math..

Computer-aided diagnostics in digital pathology: automated evaluation of early-phase pancreatic cancer in mice

Shai Dekel, Ziv Gil, Leeor Langer, 2015, International Journal of Computer Assisted Radiology and Surgery.

On Bivariate Smoothness Spaces Associated with Nonlinear Approximation

Micha Sharir, Shai Dekel, Dany Leviatan, 2004 .

A Mathematical Model for Extremely Low Dose Adaptive Computed Tomography Acquisition

Oren Barkan, Amir Averbuch, Shai Dekel, 2012, MMCS.

Adaptive Compressed Image Sensing Using Dictionaries

Amir Averbuch, Shai Dekel, Shay Deutsch, 2012, SIAM J. Imaging Sci..

Stable Support Recovery of Stream of Pulses With Application to Ultrasound Imaging

Shai Dekel, Tamir Bendory, Avinoam David Bar-Zion, 2015, IEEE Transactions on Signal Processing.

On the analysis of anisotropic smoothness

Shai Dekel, S. Dekel, 2012, J. Approx. Theory.

On the equivalence of the modulus of smoothness and the K-functional over convex domains

Shai Dekel, S. Dekel, 2010, J. Approx. Theory.

On the Relation between Piecewise Polynomial and Rational Approximation in Lp(R2)

S. Dekel, D. Leviatan, 2003 .

The Bramble-Hilbert Lemma for Convex Domains

Shai Dekel, Dany Leviatan, S. Dekel, 2004, SIAM J. Math. Anal..

Numerical Methods For PDEs Over Manifolds Using Spectral Physics Informed Neural Networks

S. Dekel, Yuval Zelig, 2023, SSRN Electronic Journal.

Beyond the Courant-Friedrichs-Lewy condition: Numerical methods for the wave problem using deep learning

Eli Turkel, Shai Dekel, Adar Kahana, 2021, J. Comput. Phys..

Hardy Spaces on ℝn with Pointwise Variable Anisotropy

P. Petrushev, S. Dekel, Tal Weissblat, 2011 .

Reverse Engineering Self-Supervised Learning

Yann LeCun, Ravid Shwartz-Ziv, S. Dekel, 2023, ArXiv.

N EAREST C LASS -C ENTER S IMPLIFICATION THROUGH I NTERMEDIATE L AYERS

S. Dekel, Ido Ben-Shaul, 2022 .

A physically-informed deep-learning model using time-reversal for locating a source from sparse and highly noisy sensors data

S. Dekel, D. Givoli, Adar Kahana, 2022, J. Comput. Phys..

Obstacle segmentation based on the wave equation and deep learning

Dan Givoli, Eli Turkel, Shai Dekel, 2020, J. Comput. Phys..

Adaptive Multivariate Approximation Using Binary Space Partitions and Geometric Wavelets

Shai Dekel, Dany Leviatan, S. Dekel, 2005, SIAM J. Numer. Anal..

Active Geometric Wavelets

Shai Dekel, Itai Gershtansky, S. Dekel, 2012 .

Sparsity-Probe: Analysis tool for Deep Learning Models pdf

Shai Dekel, Ido Ben-Shaul, S. Dekel, 2021, ArXiv.

Sparsity-Probe : 1 Analysis tool for Deep Learning Models

S. Dekel, Ido Ben-Shaul, 2021 .

Super-Resolution on the Sphere Using Convex Optimization

Shai Dekel, Tamir Bendory, Arie Feuer, 2014, IEEE Transactions on Signal Processing.

Low Bit-Rate Image Coding Using Adaptive Geometric Piecewise Polynomial Approximation

N. Dyn, S. Dekel, Roman Kazinnik, 2007, IEEE Transactions on Image Processing.

Image Coding With Geometric Wavelets

Amir Averbuch, Shai Dekel, Dror Alani, 2007, IEEE Transactions on Image Processing.

Low Bit-rate Image Coding Using Adaptive Geometric Piecewise Polynomial Approximation

N. Dyn, S. Dekel, Roman Kazinnik, 2022 .

Wavelet decompositions of non-refinable shift invariant spaces

S. Dekel, D. Leviatan, 2001 .

Machine olfaction using time scattering of sensor multiresolution graphs pdf

Yoel Shkolnisky, Shai Dekel, Leonid Gugel, 2016, ArXiv.

PR-DAD: Phase Retrieval Using Deep Auto-Decoders

S. Dekel, Leonid Gugel, 2022, 2022 7th International Conference on Frontiers of Signal Processing (ICFSP).

Function space analysis of deep learning representation layers pdf

Shai Dekel, Oren Elisha, S. Dekel, 2017, ArXiv.

Wavelet decompositions of Random Forests - smoothness analysis, sparse approximation and applications

Shai Dekel, Oren Elisha, S. Dekel, 2016, J. Mach. Learn. Res..

On Measuring the Efficiency of Kernel Operators in Lp(Rd)

Shai Dekel, Dany Leviatan, S. Dekel, 2004, Adv. Comput. Math..

Multilevel preconditioning for partition of unity methods: some analytic concepts

Wolfgang Dahmen, Shai Dekel, Pencho Petrushev, 2007, Numerische Mathematik.