On Measuring the Efficiency of Kernel Operators in Lp(Rd). - Shai Dekel; Dany Leviatan (Adv. Comput. Math., 2004)

Whitney Estimates for Convex Domains with Applications to Multivariate Piecewise Polynomial Approximation. - Shai Dekel; Dany Leviatan (Found. Comput. Math., 2004)

The Bramble-Hilbert Lemma for Convex Domains. - Shai Dekel; Dany Leviatan (SIAM J. Math. Anal., 2004)

Adaptive Multivariate Approximation Using Binary Space Partitions and Geometric Wavelets. - Shai Dekel; Dany Leviatan (SIAM J. Numer. Anal., 2005)

Multilevel preconditioning for partition of unity methods: some analytic concepts. - Wolfgang Dahmen; Shai Dekel; Pencho Petrushev (Numerische Mathematik, 2007)

Image Coding With Geometric Wavelets. - Dror Alani; Amir Averbuch; Shai Dekel (IEEE Trans. Image Process., 2007)

Low Bit-Rate Image Coding Using Adaptive Geometric Piecewise Polynomial Approximation. - Roman Kazinnik; Shai Dekel; Nira Dyn (IEEE Trans. Image Process., 2007)

On the equivalence of the modulus of smoothness and the K-functional over convex domains. - Shai Dekel (J. Approx. Theory, 2010)

A Mathematical Model for Extremely Low Dose Adaptive Computed Tomography Acquisition. - Oren Barkan; Amir Averbuch; Shai Dekel; Yaniv Tenzer (MMCS, 2012)

On the analysis of anisotropic smoothness. - Shai Dekel (J. Approx. Theory, 2012)

Adaptive Compressed Image Sensing Using Dictionaries. - Amir Averbuch; Shai Dekel; Shay Deutsch (SIAM J. Imaging Sci., 2012)

Adaptive Compressed Tomography Sensing. - Oren Barkan; Jonathan Weill; Amir Averbuch; Shai Dekel (CVPR, 2013)

Robust Recovery of Stream of Pulses using Convex Optimization. - Tamir Bendory; Shai Dekel; Arie Feuer (CoRR, 2014)

Exact recovery of Dirac ensembles from the projection onto spaces of spherical harmonics. - Tamir Bendory; Shai Dekel; Arie Feuer (CoRR, 2014)

Exact recovery of non-uniform splines from the projection onto spaces of algebraic polynomials. - Tamir Bendory; Shai Dekel; Arie Feuer (J. Approx. Theory, 2014)

Computer-aided diagnostics in digital pathology: automated evaluation of early-phase pancreatic cancer in mice. - Leeor Langer; Yoav Binenbaum; Leonid Gugel; Moran Amit; Ziv Gil; Shai Dekel (Int. J. Comput. Assist. Radiol. Surg., 2015)

Unified Convex Optimization Approach to Super-Resolution Based on Localized Kernels. - Tamir Bendory; Shai Dekel; Arie Feuer (CoRR, 2015)

Super-Resolution on the Sphere Using Convex Optimization. - Tamir Bendory; Shai Dekel; Arie Feuer (IEEE Trans. Signal Process., 2015)

Machine olfaction using time scattering of sensor multiresolution graphs. - Leonid Gugel; Yoel Shkolnisky; Shai Dekel (CoRR, 2016)

Wavelet decompositions of Random Forests - smoothness analysis, sparse approximation and applications. - Oren Elisha; Shai Dekel (J. Mach. Learn. Res., 2016)

Stable Support Recovery of Stream of Pulses With Application to Ultrasound Imaging. - Tamir Bendory; Avinoam David Bar-Zion; Dan Adam; Shai Dekel; Arie Feuer (IEEE Trans. Signal Process., 2016)

Function space analysis of deep learning representation layers. - Oren Elisha; Shai Dekel (CoRR, 2017)

A Mathematical Model for Adaptive Computed Tomography Sensing. - Oren Barkan; Jonathan Weill; Shai Dekel; Amir Averbuch (IEEE Trans. Computational Imaging, 2017)

Wavelet Decomposition of Gradient Boosting. - Shai Dekel; Oren Elisha; Ohad Morgan (CoRR, 2018)

Obstacle segmentation based on the wave equation and deep learning. - Adar Kahana; Eli Turkel; Shai Dekel; Dan Givoli (J. Comput. Phys., 2020)

Sparsity-Probe: Analysis tool for Deep Learning Models. - Ido Ben-Shaul; Shai Dekel (CoRR, 2021)

Beyond the Courant-Friedrichs-Lewy condition: Numerical methods for the wave problem using deep learning. - Oded Ovadia; Adar Kahana; Eli Turkel; Shai Dekel (J. Comput. Phys., 2021)

PR-DAD: Phase Retrieval Using Deep Auto-Decoders. - Shai Dekel; Leon Gugel (ICFSP, 2022)

Nearest Class-Center Simplification through Intermediate Layers. - Ido Ben-Shaul; Shai Dekel (TAG-ML, 2022)

A physically-informed deep-learning model using time-reversal for locating a source from sparse and highly noisy sensors data. - Adar Kahana; Eli Turkel; Shai Dekel; Dan Givoli (J. Comput. Phys., 2022)

Reverse Engineering Self-Supervised Learning. - Ido Ben-Shaul; Ravid Shwartz-Ziv; Tomer Galanti; Shai Dekel; Yann LeCun (NeurIPS, 2023)

Numerical Methods For PDEs Over Manifolds Using Spectral Physics Informed Neural Networks. - Yuval Zelig; Shai Dekel (CoRR, 2023)

Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. - Ido Ben-Shaul; Tomer Galanti; Shai Dekel (Trans. Mach. Learn. Res., 2023)

Wavelets Are All You Need for Autoregressive Image Generation. - Wael Mattar; Idan Levy; Nir Sharon; Shai Dekel (CoRR, 2024)