D. Donoho

I. Johnstone, D. Donoho, D. Donoho, 1994, Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

CART AND BEST-ORTHO-BASIS: A CONNECTION'

D. Donoho, 1997 .

Wavelet Shrinkage and W.V.D.: A 10-minute tour

D. Donoho, 1997 .

Higher criticism thresholding: Optimal feature selection when useful features are rare and weak

D. Donoho, Jiashun Jin, 2008, Proceedings of the National Academy of Sciences.

On Minimum Entropy Segmentation

D. Donoho, 1994 .

Minimax risk over / p-balls for / q-error

D. Donoho, M. Johnstone, 2022 .

Can recent innovations in harmonic analysis `explain' key findings in natural image statistics?

A. G. Flesia, D. Donoho, 2001, Network.

One-sided inference about functionals of a density

D. Donoho, 1988 .

Fast and accurate Polar Fourier transform

D. Donoho, A. Averbuch, R. Coifman, 2006 .

Estimating Covariances of Locally Stationary Processes : Rates of Convergence of Best Basis Methods

S. Mallat, D. Donoho, R. V. Sachs, 1998 .

Continuous curvelet transform: II. Discretization and frames

E. Candès, D. Donoho, 2005 .

Uncertainty principles and ideal atomic decomposition

Xiaoming Huo, David L. Donoho, D. Donoho, 2001, IEEE Trans. Inf. Theory.

The quasi-periodic oscillations and very low frequency noise of Scorpius X-1 as transient chaos - A dripping handrail?

D. Donoho, J. Crutchfield, J. Scargle, 1993 .

Sparse Solution Of Underdetermined Linear Equations By Stagewise Orthogonal Matching Pursuit

David L. Donoho, D. Donoho, 2006 .

Asymptotic Minimaxity Of False Discovery Rate Thresholding For Sparse Exponential Data

D. Donoho, Jiashun Jin, 2006, math/0602311.

Deslauries-Dubuc: Ten years after

D. Donoho, T. Yu, 1999 .

NATURE VS . MATH : INTERPRETING INDEPENDENT COMPONENT ANALYSIS IN LIGHT OF COMPUTATIONAL HARMONIC ANALYSIS

D. Donoho, 2000 .

High-Dimensional Centrally Symmetric Polytopes with Neighborliness Proportional to Dimension

David L. Donoho, D. Donoho, 2006, Discret. Comput. Geom..

MCALab: Reproducible Research in Signal and Image Decomposition and Inpainting

Michael Elad, Mohamed-Jalal Fadili, Jean-Luc Starck, 2010, Computing in Science & Engineering.

An information-theoretic approach to traffic matrix estimation

Carsten Lund, Yin Zhang, Matthew Roughan, 2003, SIGCOMM '03.

Does median filtering truly preserve edges better than linear filtering

D. Donoho, E. Arias-Castro, 2006, math/0612422.

Variance Breakdown of Huber (M)-estimators: $n/p \rightarrow m \in (1,\infty)$

D. Donoho, A. Montanari, 2015, 1503.02106.

Variance Breakdown of Huber ( M )-estimators : n / p → m ∈ ( 1 , ∞ )

D. Donoho, A. Montanari, 2015 .

Neo-classical minimax problems, thresholding and adaptive function estimation

I. Johnstone, D. Donoho, 1996 .

Morphological Component Analysis: An Adaptive Thresholding Strategy

Mohamed-Jalal Fadili, Jean-Luc Starck, David L. Donoho, 2007, IEEE Transactions on Image Processing.

Ideal spacial adaptation via wavelet shrinkage

D. L. Donoho, D. Donoho, 1994 .

Data Compression and Harmonic Analysis

Martin Vetterli, Ronald A. DeVore, Ingrid Daubechies, 1998, IEEE Trans. Inf. Theory.

Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising

Andrea Montanari, David L. Donoho, Iain Johnstone, 2011, IEEE Transactions on Information Theory.

Message passing algorithms for compressed sensing: I. motivation and construction

Andrea Montanari, Arian Maleki, David L. Donoho, 2009, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo).

How to Design Message Passing Algorithms for Compressed Sensing

D. Donoho, A. Montanari, A. Maleki, 2011 .

Counting the Faces of Randomly-Projected Hypercubes and Orthants, with Applications

David L. Donoho, Jared Tanner, D. Donoho, 2008, Discret. Comput. Geom..

Stable recovery of sparse overcomplete representations in the presence of noise

Michael Elad, Vladimir N. Temlyakov, David L. Donoho, 2006, IEEE Transactions on Information Theory.

Multiscale Stepping-Stone Detection: Detecting Pairs of Jittered Interactive Streams by Exploiting Maximum Tolerable Delay

Vern Paxson, Stuart Staniford-Chen, Umesh Shankar, 2002, RAID.

SPIR-iT : Autocalibrating Parallel Imaging Compressed Sensing

D. Donoho, M. Lustig, J. Pauly, 2008 .

High-resolution navigation on non-differentiable image manifolds

Richard G. Baraniuk, Michael B. Wakin, Hyeokho Choi, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Digital Implementation of Ridgelet Packets

A. G. Flesia, E. Candès, D. Donoho, 2003 .

Multiscale Geometric Analysis for 3-D Catalogues

D. Donoho, J. Starck, O. Levi, 2002 .

Fast Solution of $\ell _{1}$ -Norm Minimization Problems When the Solution May Be Sparse

Yaakov Tsaig, David L. Donoho, D. Donoho, 2008, IEEE Transactions on Information Theory.

From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images

Michael Elad, Alfred M. Bruckstein, David L. Donoho, 2009, SIAM Rev..

Renormalization Exponents and Optimal Pointwise Rates of Convergence

D. Donoho, Mark G. Low, 1992 .

APPLICATIONS OF BEAMLETS TO DETECTION AND EXTRACTION OF LINES , CURVES AND OBJECTS IN VERY NOISY IMAGES

D. Donoho, 2001 .

Neural Proximal Gradient Descent for Compressive Imaging

Morteza Mardani, Qingyun Sun, Hatef Monajemi, 2018, NeurIPS.

Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery

D. Donoho, J. Pauly, S. Vasanawala, 2017, ArXiv.

Years of Data Science

D. Donoho, 2017 .

A fast wavelet algorithm for image deblurring

D. L. Donoho, D. Donoho, M. Raimondo, 2005 .

Smooth Multiwavelet Duals of Alpert Bases by Moment-Interpolating Refinement

D. Donoho, D. Levin, N. Dyn, 2000 .

Breakdown of equivalence between the minimal l1-norm solution and the sparsest solution

Yaakov Tsaig, David L. Donoho, D. Donoho, 2006, Signal Process..

Morphological Component Analysis : new Results

D. Donoho, J. Fadili, J. Starck, 2006 .

Convex Sparse Blind Deconvolution: Phase Transition, Observation Sample Complexity, Stability, Robustness

D. Donoho, Qingyun Sun, 2020 .

practical results can be achieved with a very small number of images.

D. Donoho, J. Tanner, Jared Tanner, 2010 .

Precise Undersampling Theorems

D. Donoho, J. Tanner, Jared Tanner, 2010, Proceedings of the IEEE.

Pathologies of some Minimum Distance Estimators

D. Donoho, Richard C. Liu, 1988 .

Sparsity and the Bayesian perspective

D. Donoho, J. Starck, A. Rassat, 2013, 1302.2758.

Maximum entropy reconstruction of complex (phase-sensitive) spectra

I. Johnstone, D. Donoho, A. Stern, 1990 .

Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices

Sina Jafarpour, Hatef Monajemi, Matan Gavish, 2012, Proceedings of the National Academy of Sciences.

Morphology of the galaxy distribution from wavelet denoising

D. Donoho, J. Starck, V. Martínez, 2005, astro-ph/0508326.

Does the maximum entropy method improve sensitivity?

A S Stern, J C Hoch, I. Johnstone, 1990, Proceedings of the National Academy of Sciences of the United States of America.

Neighborly Polytopes And Sparse Solution Of Underdetermined Linear Equations

David L. Donoho, D. Donoho, 2005 .

Recovery Based on Kolmogorov Complexity in Underdetermined Systems of Linear Equations

D. Donoho, H. Kakavand, J. Mammen, 2022 .

OPTIMAL SHRINKAGE OF SINGULAR VALUES By Matan Gavish

D. Donoho, M. Gavish, 2014 .

Wavelet applications VIII : 18-20 April 2001, Orlando, USA

Harold H. Szu, James R. Buss, David L. Donoho, 2001 .

Adapting to Unknown Smoothness via Wavelet Shrinkage

I. Johnstone, D. Donoho, 1995 .

Wavelet shrinkage techniques for images

D. Donoho, Michael Elad, Boaz Matalon, 2020 .

Robust nonlinear wavelet transform based on median-interpolation

Tao Yu, D. Donoho, D.L. Donoho, 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

Special issue on diffusion maps and wavelets

Charles K. Chui, David L. Donoho, C. Chui, 2006 .

1 Universal Near Minimaxity of Wavelet Shrinkage

I. Johnstone, D. Donoho, G. Kerkyacharian, 1999 .

Wavelet Applications VIII

Harold H. Szu, James R. Buss, David L. Donoho, 1996 .

A RATIONAL DESIGN OF A DIGITAL SHEARLET TRANSFORM

D. Donoho, G. Kutyniok, X. Zhuang, 2010 .

A Universal Identifier for Computational Results

David L. Donoho, Matan Gavish, D. Donoho, 2011, ICCS.

Universal Near Minimaxity of

I. Johnstone, D. Donoho, G. Kerkyacharian, 1997 .

Neo-Classical Minimax Problems , Thresholding , and Adaptation

I. Johnstone, D. Donoho, 1994 .

Hessian Eigenmaps : new locally linear embedding techniques for high-dimensional data

D. Donoho, C. Grimes, Hessian Eigenmaps, 2003 .

Renormalizing Experiments for Nonlinear Functionals

D. Donoho, 1997 .

Is Patience a Virtue? The Unsentimental Case for the Long View in Evaluating Returns

D. Donoho, Robert A. Crenian, Matthew H. Scanlan, 2010, The Journal of Portfolio Management.

NUScon: A community-driven platform for quantitative evaluation of nonuniform sampling in NMR

Adam D. Schuyler, Jeffrey C. Hoch, Robert Powers, 2021, Magnetic Resonance.

Incoherence of Partial-Component Sampling in multidimensional NMR

D. Donoho, J. Hoch, A. Schuyler, 2017, 1702.01830.

A First Course in Wavelets with Fourier Analysis

David L. Donoho, Paul L. Donoho, D. Donoho, 2002 .

The Curvelet Transform for Image

David L. Donoho, D. Donoho, DenoisingJean-Lu Star, 2000 .

Connect the dots: how many random points can a regular curve pass through?

Craig A. Tovey, Xiaoming Huo, David L. Donoho, 2005, Advances in Applied Probability.

Dynamic Programming Methods for “ Connect the Dots ” in Scattered Point Clouds

D. Donoho, E. Arias-Castro, C. Tovey, 2007 .

Adaptive Multiscale Detection of Smooth Curves Embedded in a Background of Uniform Random Points

D. Donoho, E. Arias-Castro, X. Huo, 2003 .

Dear Information and Inference Reader

John Shawe-Taylor, David L. Donoho, Jared Tanner, 2012 .

Recovering edges in ill-posed inverse problems: optimality of curvelet frames

E. Candès, D. Donoho, 2002 .

Nonlinear Pyramid Transforms Based on Median-Interpolation

David L. Donoho, Thomas Pok-Yin Yu, D. Donoho, 2000, SIAM J. Math. Anal..

In Wavelets and Statistics

Ronald R. Coifman, David L. Donoho, D. Donoho, 1995 .

A note on rearrangements, spectral concentration, and the zero-order prolate spheroidal wavefunction

Philip B. Stark, David L. Donoho, D. Donoho, 1993, IEEE Trans. Inf. Theory.

Data Display 51 e MacSpin: Dynamic Graphics on a Desktop Computer

David L. Donoho, Andrew W. Donoho, Miriam Gasko, 1988 .

When does geodesic distance recover the true hidden parametrization of families of articulated images?

David L. Donoho, Carrie Grimes, D. Donoho, 2002, The European Symposium on Artificial Neural Networks.

Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path pdf

David L. Donoho, Vardan Papyan, X. Y. Han, 2021, ArXiv.

Discussion: Projection Pursuit

Werner A. Stahel, Peter J. Rousseeuw, David L. Donoho, 1985 .

The Impossibility Region for Detecting Sparse Mixtures using the Higher Criticism

Alon Kipnis, David L. Donoho, D. Donoho, 2021, 2103.03218.

Translation-Invariant DeNoising

D. Donoho, R. Coifman, 1995 .

Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path

X. Y. Han, D. Donoho, V. Papyan, 2021, ICLR.

Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences

D. Donoho, A. Kipnis, 2020, The Annals of Statistics.

CART AND BEST-ORTHO-BASIS: A CONNECTION 1

D. Donoho, 1997 .

Correction: Connect the dots: how many random points can a regular curve pass through?

D. Donoho, E. Arias-Castro, C. Tovey, 2006, math/0603673.

Higher criticism for detecting sparse heterogeneous mixtures

D. Donoho, Jiashun Jin, 2004, math/0410072.

Morphology of the Galaxy Distribution from Wavelet Denoising

D. Donoho, J. Starck, V. Martínez, 2005, astro-ph/0508326.

CAN A REGULAR CURVE PASS THROUGH

D. Donoho, E. Arias-Castro, 2005 .

ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise

D. Donoho, M. Gavish, Elad Romanov, 2020, 2009.12297.

Adapting to unknown sparsity by controlling the false discovery rate

I. Johnstone, D. Donoho, Y. Benjamini, 2005, math/0505374.

ADAPTIVE MULTISCALE DETECTION OF FILAMENTARY STRUCTURES IN A BACKGROUND OF UNIFORM RANDOM POINTS 1

D. Donoho, E. Arias-Castro, X. Huo, 2006, math/0605513.

Asymptotic Minimaxity Of False Discovery Rate Thresholding For Sparse Exponential Data

D. Donoho, Jiashun Jin, 2006, math/0602311.

Multiscale morphology of the galaxy distribution

D. Donoho, Jean-Luc Starck, V. Martínez, 2006, astro-ph/0610958.

Analysis of the Spatial Distribution of Galaxies by Multiscale Methods

D. Donoho, Jean-Luc Starck, P. Querre, 2004, EURASIP J. Adv. Signal Process..

Optimal Eigenvalue Shrinkage in the Semicircle Limit

D. Donoho, M. J. Feldman, 2022, 2210.04488.

New Computational Challenges in Cosmology a Proposal Submitted to the Nsf Kdi New Computational Challenges Program

D. Donoho, N. Aghanim, J. Silk, 2022 .

Emerging applications of geometric multiscale analysis

D. Donoho, 2002, math/0212395.

DENSITY ESTIMATION BY WAVELET THRESHOLDING 1

I. Johnstone, D. Donoho, G. Kerkyacharian, 2022 .

High dimensional robust M-estimation: asymptotic variance via approximate message passing

D. Donoho, A. Montanari, 2015, Probability Theory and Related Fields.

Information-theoretically optimal compressed sensing via spatial coupling and approximate message passing

D. Donoho, Adel Javanmard, A. Montanari, 2013, 2012 IEEE International Symposium on Information Theory Proceedings.

The Optimal Hard Threshold for Singular Values is 4 / √ 3

D. Donoho, M. Gavish, 2013 .

Abstract Statistical Estimation and Modern Harmonic Analysis

D. Donoho, 1995 .

Aide-Memoire . High-Dimensional Data Analysis : The Curses and Blessings of Dimensionality

David L. Donoho, D. Donoho, 2000 .

Multiscale representation for data on the sphere and applications to geopotential data

Jean-Luc Starck, David L. Donoho, Morteza Shahram, 2007, SPIE Optical Engineering + Applications.

Message passing algorithms for compressed sensing: II. analysis and validation

Andrea Montanari, Arian Maleki, David L. Donoho, 2009, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo).

Optimal Shrinkage of Singular Values

David L. Donoho, Matan Gavish, D. Donoho, 2014, IEEE Transactions on Information Theory.

Prevalence of neural collapse during the terminal phase of deep learning training

David L. Donoho, Vardan Papyan, X. Y. Han, 2020, Proceedings of the National Academy of Sciences.

Scanning the Technology

David L. Donoho, D. Donoho, 2010, Proc. IEEE.

Measuring the predictive performance of computer-controlled infusion pumps

Steven L. Shafer, David L. Donoho, John R. Varvel, 1992, Journal of Pharmacokinetics and Biopharmaceutics.

The Kolmogorov Sampler

David L. Donoho, D. Donoho, 2002 .

The science of deep learning

Richard Baraniuk, David Donoho, Matan Gavish, 2020, Proceedings of the National Academy of Sciences.

Wavelet analysis [for signal processing]

Hong-Ye Gao, A. Bruce, D. Donoho, 1996 .

Two-sample Testing for Large, Sparse High-Dimensional Multinomials under Rare/Weak Perturbations

D. Donoho, A. Kipnis, 2020 .

Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit

Jean-Luc Starck, Yaakov Tsaig, David L. Donoho, 2012, IEEE Transactions on Information Theory.

Feature selection by higher criticism thresholding achieves the optimal phase diagram

Jiashun Jin, David Donoho, D. Donoho, 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Breakdown Point of Model Selection When the Number of Variables Exceeds the Number of Observations

Victoria Stodden, David L. Donoho, D. Donoho, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

HIGHER CRITICISM FOR DETECTING SPARSE HETEROGENEOUS MIXTURES1 BY DAVID DONOHO

D. Donoho, Jiashun Jin, 2004 .

Higher Criticism for Large-Scale Inference: especially for Rare and Weak effects

Jiashun Jin, David Donoho, D. Donoho, 2014, 1410.4743.

Reproducible Research in Computational Harmonic Analysis

Arian Maleki, Victoria Stodden, David L. Donoho, 2009, Computing in Science & Engineering.

Virtual Northern Analysis of the Human Genome

D. Donoho, P. Brown, V. Stodden, 2007, PLoS biology.

WaveLab and Reproducible Research

David L. Donoho, Jonathan B. Buckheit, D. Donoho, 1995 .

Compressed Sensing MRI

M. Lustig, D.L. Donoho, J.M. Santos, 2008, IEEE Signal Processing Magazine.

The curvelet transform for image denoising

Emmanuel J. Candès, E. Candès, D. Donoho, 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

Digital curvelet transform: strategy, implementation, and experiments

David L. Donoho, Mark R. Duncan, D. Donoho, 2000, SPIE Defense + Commercial Sensing.

Curvelets and Curvilinear Integrals

Emmanuel J. Candès, David L. Donoho, E. Candès, 2001, J. Approx. Theory.

Hardest One-Dimensional Subproblems

David L. Donoho, D. Donoho, Richard C. Liu, 2008 .

NMR data processing using iterative thresholding and minimum l(1)-norm reconstruction.

David L Donoho, Jeffrey C Hoch, Alan S Stern, 2007, Journal of magnetic resonance.

Fast Discrete Curvelet Transforms

Laurent Demanet, Lexing Ying, Emmanuel J. Candès, 2006, Multiscale Model. Simul..

Submitted to Ieee Transactions on Image Processing Image Decomposition via the Combination of Sparse Representations and a Variational Approach

Michael Elad, Jean-Luc Starck, David L. Donoho, 2022 .

Multiscale geometric analysis for 3D catalogs

Jean-Luc Starck, Ofer Levi, David L. Donoho, 2002, SPIE Astronomical Telescopes + Instrumentation.

Cosmological Non-Gaussian Signature Detection: Comparing Performance of Different Statistical Tests

Jean-Luc Starck, Jiashun Jin, David L. Donoho, 2005, EURASIP J. Adv. Signal Process..

Interpolating Wavelet Transforms

David L. Donoho, D. Donoho, 1992 .

Nonlinear Wavelet Methods for Recovery of Signals, Densities, and Spectra from Indirect and Noisy Da

David L. Donoho, D. Donoho, 1993 .

Compressed Sensing over ℓp-balls: Minimax mean square error

Andrea Montanari, Arian Maleki, David L. Donoho, 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

Denoising and robust nonlinear wavelet analysis

David L. Donoho, Andrew G. Bruce, Hong-Ye Gao, 1994, Defense, Security, and Sensing.

Smoothing and Robust Wavelet Analysis

R. Douglas Martin, David L. Donoho, Andrew G. Bruce, 1994 .

Tight frames of k-plane ridgelets and the problem of representing objects that are smooth away from d-dimensional singularities in Rn.

D. Donoho, D L Donoho, 1999, Proceedings of the National Academy of Sciences of the United States of America.

What’s Missing from Today’s Machine Intelligence Juggernaut?

D. Donoho, 2019 .

Curvelets, multiresolution representation, and scaling laws

David L. Donoho, Emmanuel J. Candes, E. Candès, 2000, SPIE Optics + Photonics.

Orthonormal Ridgelets and Linear Singularities

David L. Donoho, D. Donoho, 2000, SIAM J. Math. Anal..

Extensions of compressed sensing

Yaakov Tsaig, David L. Donoho, D. Donoho, 2006, Signal Process..

Curvelets and reconstruction of images from noisy radon data

David L. Donoho, Emmanuel J. Candes, E. Candès, 2000, SPIE Optics + Photonics.

Microlocal Analysis of the Geometric Separation Problem pdf

Gitta Kutyniok, David L. Donoho, D. Donoho, 2010, ArXiv.

Geometric Separation using a Wavelet-Shearlet Dictionary

Gitta Kutyniok, David L. Donoho, D. Donoho, 2010 .

Development of a digital shearlet transform based on Pseudo-Polar FFT

Gitta Kutyniok, David L. Donoho, Morteza Shahram, 2009, Optical Engineering + Applications.

Analysis of lscr1 minimization in the Geometric Separation Problem

Gitta Kutyniok, David L. Donoho, D. Donoho, 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

High dimensional robust M-estimation: asymptotic variance via approximate message passing

Andrea Montanari, David L. Donoho, D. Donoho, 2013, Probability Theory and Related Fields.

The Optimal Hard Threshold for Singular Values is 4/sqrt(3)

David L. Donoho, Matan Gavish, D. Donoho, 2013, 1305.5870.

The Simplest Solution to an Underdetermined System of Linear Equations

David L. Donoho, Hossein Kakavand, James Mammen, 2006, 2006 IEEE International Symposium on Information Theory.

Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing

Adel Javanmard, Andrea Montanari, David L. Donoho, 2011, IEEE Transactions on Information Theory.

Examples of basis pursuit

Scott Chen, David L. Donoho, D. Donoho, 1995, Optics + Photonics.

Achieving Bayes MMSE performance in the sparse signal + Gaussian white noise model when the noise level is unknown

Galen Reeves, David L. Donoho, D. Donoho, 2013, 2013 IEEE International Symposium on Information Theory.

Multiscale Representations for Manifold-Valued Data

Peter Schröder, Victoria Stodden, David L. Donoho, 2005, Multiscale Model. Simul..

A Framework for Discrete Integral Transformations I-The Pseudopolar Fourier Transform

Ronald R. Coifman, Yoel Shkolnisky, Amir Averbuch, 2008, SIAM J. Sci. Comput..

Accurate and fast discrete polar Fourier transform

Michael Elad, Ronald R. Coifman, Amir Averbuch, 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

Fast Slant Stack: a Notion of Radon Transform for Data in a Cartesian Grid Which Is Rapidly Computible, Algebraically Exact, Geometrically Faithful and Invertible

Ronald R. Coifman, Amir Averbuch, Moshe Israeli, 2001 .

ScreeNOT: Exact MSE-optimal singular value thresholding in correlated noise

D. Donoho, M. Gavish, Elad Romanov, 2020, The Annals of Statistics.

Image decomposition: separation of texture from piecewise smooth content

Jean-Luc Starck, David L. Donoho, Mikael Elad, 2003, SPIE Optics + Photonics.

A Framework for Discrete Integral Transformations II-The 2D Discrete Radon Transform

Ronald R. Coifman, Yoel Shkolnisky, Amir Averbuch, 2008, SIAM J. Sci. Comput..

An invitation to reproducible computational research.

David L Donoho, D. Donoho, 2010, Biostatistics.

The multiscale structure of non-differentiable image manifolds

Richard G. Baraniuk, Michael B. Wakin, Hyeokho Choi, 2005, SPIE Optics + Photonics.

Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing

Arian Maleki, David L. Donoho, D. Donoho, 2009, IEEE Journal of Selected Topics in Signal Processing.

Morphological component analysis

J. Bobin, Y. Moudden, J.-L. Starck, 2005, SPIE Optics + Photonics.

Beamlet pyramids: a new form of multiresolution analysis suited for extracting lines, curves, and objects from very noisy image data

Xiaoming Huo, David L. Donoho, D. Donoho, 2000, SPIE Optics + Photonics.

A RATIONAL DESIGN OF A DIGITAL SHEARLET TRANSFORM

D. Donoho, G. Kutyniok, X. Zhuang, 2010 .

Convex Sparse Blind Deconvolution pdf

Qingyun Sun, David Donoho, D. Donoho, 2021, ArXiv.

The phase transition of matrix recovery from Gaussian measurements matches the minimax MSE of matrix denoising

Andrea Montanari, David L. Donoho, Matan Gavish, 2013, Proceedings of the National Academy of Sciences.

Beamlets and Multiscale Image Analysis

Xiaoming Huo, David L. Donoho, D. Donoho, 2002 .

Multiscale detection of filamentary features in image data

Xiaoming Huo, David L. Donoho, Jihong Chen, 2003, SPIE Optics + Photonics.

Near-optimal detection of geometric objects by fast multiscale methods

Xiaoming Huo, David L. Donoho, Ery Arias-Castro, 2005, IEEE Transactions on Information Theory.

Fast X-Ray and Beamlet Transforms for Three-Dimensional Data

David L. Donoho, Ofer Levi, D. Donoho, 2002 .

Recovering layers of brush strokes through statistical analysis of color and shape: an application to van Gogh's Self portrait with grey felt hat

David G. Stork, David L. Donoho, Morteza Shahram, 2008, Electronic Imaging.

Precise Undersampling Theorems

David L. Donoho, Jared Tanner, D. Donoho, 2010, Proceedings of the IEEE.

Beamlab and Reproducible Research

Xiaoming Huo, David L. Donoho, D. Donoho, 2004, Int. J. Wavelets Multiresolution Inf. Process..

Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery pdf

Morteza Mardani, David L. Donoho, Hatef Monajemi, 2017, ArXiv.

Dream applications of verifiable computational results

David L. Donoho, Matan Gavish, Amos Onn, 2013, XRDS.

Three Dream Applications of Verifiable Computational Results

David L. Donoho, Matan Gavish, D. Donoho, 2012, Computing in Science & Engineering.

Minimax quadratic estimation of a quadratic functional

Michael Nussbaum, David L. Donoho, M. Nussbaum, 1990, J. Complex..

Optimal Covariance Estimation for Condition Number Loss in the Spiked Model.

David L. Donoho, Behrooz Ghorbani, D. Donoho, 2018, 1810.07403.

k-t SPARSE: High frame rate dynamic MRI exploiting spatio-temporal sparsity

Michael Lustig, David L. Donoho, John M. Pauly, 2006 .

Implications for Image Watermarking of Recent Work in Image Analysis and Representation

David L. Donoho, Ana Georgina Flesia, A. G. Flesia, 2002, IWDW.

The Use of Kinematic Displays to Represent High Dimensional Data

Peter J. Huber, David Donoho, Hans-Mathis Thoma, 1981 .

Universal Near Minimaxity of Wavelet Shrinkage

I. Johnstone, D. Donoho, G. Kerkyacharian, 1997 .

Image Manifolds which are Isometric to Euclidean Space

David L. Donoho, Carrie Grimes, D. Donoho, 2005, Journal of Mathematical Imaging and Vision.

Principled and interpretable alignability testing and integration of single-cell data

D. Donoho, James Zou, Eric D. Sun, 2023, bioRxiv.

Improved linear discrimination using time-frequency dictionaries

David L. Donoho, Jonathan B. Buckheit, D. Donoho, 1995, Optics + Photonics.

High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality

Gregory Piatetsky-Shapiro, Elder, A. G. Flesia, 2000 .

Compressed sensing

D. L. Donoho, D. Donoho, 2006, IEEE Trans. Inf. Theory.

Degrees of Freedom Analysis of Unrolled Neural Networks pdf

Morteza Mardani, Qingyun Sun, David Donoho, 2019, ArXiv.

On the stability of the basis pursuit in the presence of noise

Michael Elad, David L. Donoho, D. Donoho, 2006, Signal Process..

Faster Imaging with Randomly Perturbed, Undersampled Spirals and |L|_1 Reconstruction

Michael Lustig, David L. Donoho, Jin Hyung Lee, 2004 .

Rapid MR Imaging with "Compressed Sensing" and Randomly Under-Sampled 3DFT Trajectories

D. L. Donoho, M. Lustig, J. M. Pauly, 2004 .

Solution of l1Minimization Problems by LARS/Homotopy Methods

David L. Donoho, Iddo Drori, D. Donoho, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Characteristics of Network Delays in Wide Area File Transfers

Paul Barford, David L. Donoho, Ana Georgina Flesia, 2002 .

Minimax Risk for Hyperrectangles

D. Donoho, 2008 .

Neo-Classical Minimax Problems , Thresholding , and Adaptation

I. Johnstone, D. Donoho, 1994 .

Gel ' fand n-Widths and the Method of Least Squares

D. Donoho, 2008 .

AI and the Digitized Photoarchive

D. Donoho, V. Papyan, C. R. Johnson, 2021, Art Documentation: Journal of the Art Libraries Society of North America.

On denoising and best signal representation

Stéphane Mallat, Hamid Krim, David L. Donoho, 1999, IEEE Trans. Inf. Theory.

Best basis algorithm for signal enhancement

Stéphane Mallat, Alan S. Willsky, Hamid Krim, 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

Very high quality image restoration by combining wavelets and curvelets

Jean-Luc Starck, David L. Donoho, Emmanuel J. Candes, 2001, SPIE Optics + Photonics.

Extensions of compressed sensing

D. Donoho, Yaakov Tsaig, 2006, Signal Process..

Super-resolution and reconstruction of sparse sub-wavelength images

D. Donoho, M. Zibulevsky, M. Segev, 2022 .

Sparsity Based Sub-wavelength Imaging with Partially Incoherent Light via Quadratic Compressed Sensing References and Links

Yonina C. Eldar, Yoav Shechtman, Alexander Szameit, 2022 .

Estimating point-to-point and point-to-multipoint traffic matrices: an information-theoretic approach

Carsten Lund, Yin Zhang, Matthew Roughan, 2005, IEEE/ACM Transactions on Networking.

Higher criticism to compare two large frequency tables, with sensitivity to possible rare and weak differences

D. Donoho, A. Kipnis, 2020, The Annals of Statistics.

On the Inability of the Higher Criticism to Detect Rare/Weak Departures

D. Donoho, A. Kipnis, 2021 .

15 Years of Reproducible Research in Computational Harmonic Analysis

Arian Maleki, Victoria Stodden, David L. Donoho, 2008 .

On Minimax Estimation of Linear Functionals

D. Donoho, Richard C. Liu, 2008 .

When do libraries of articulated images obey an isometric embedding ?

D. Donoho, C. Grimes, 2003 .

A Framework for Discrete Integral Transformations Ii – the 2d Discrete Radon Transform

D. Donoho, A. Averbuch, R. Coifman, 2022 .

The Optimal Hard Threshold for Singular Values is $4/\sqrt {3}$

D. Donoho, M. Gavish, 2014, IEEE Transactions on Information Theory.

Application of basis pursuit in spectrum estimation

David L. Donoho, Scott Saobing Chen, D. Donoho, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Convolutional Imputation of Matrix Networks

Stephen P. Boyd, David L. Donoho, Qingyun Sun, 2016, ICML.

Leaf fossil record suggests limited influence of atmospheric CO2 on terrestrial productivity prior to angiosperm evolution

S. Fienberg, D. Donoho, P. Hanawalt, 2012, Proceedings of the National Academy of Sciences.

Image decomposition via the combination of sparse representations and a variational approach

D. Donoho, Jean-Luc Starck, Michael Elad, 2005, IEEE Transactions on Image Processing.

Systems Neuroscience

S. Fienberg, D. Kiper, D. Donoho, 2018, Advances in Neurobiology.

Some experiments on independent component analysis of non-Gaussian processes

Jean-Francois Cardoso, D. L. Donoho, D. Donoho, 1999, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics. SPW-HOS '99.

MacSpin: dynamic graphics on a desktop computer

David L. Donoho, Andrew W. Donoho, Mitiam Gasko, 1988, IEEE Computer Graphics and Applications.

Systems Neuroscience

S. Fienberg, D. Donoho, P. Hanawalt, 2018, Advances in Neurobiology.

Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data

D. Donoho, Sanmi Koyejo, Rylan Schaeffer, 2024, 2404.01413.

A Framework for Discrete Integral Transformations II-The 2D Discrete Radon Transform

D. Donoho, Y. Shkolnisky, I. Sedelnikov, 2008, SIAM J. Sci. Comput..

A Framework for Discrete Integral Transformations I-The Pseudopolar Fourier Transform

D. Donoho, Y. Shkolnisky, A. Averbuch, 2008, SIAM Journal on Scientific Computing.

Fast spiral Fourier transform for iterative MR image reconstruction

Jin Hyung Lee, D. Donoho, M. Lustig, 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

Multiscale geometric analysis of three-dimensional data

David L. Donoho, Ofer Levi, D. Donoho, 2004 .

Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ1 minimization

D. Donoho, Michael Elad, 2003, Proceedings of the National Academy of Sciences of the United States of America.

The Optimal Hard Threshold for Singular Values is 4/sqrt(3)

D. Donoho, M. Gavish, 2013 .

Message-passing algorithms for compressed sensing

D. Donoho, A. Montanari, A. Maleki, 2009, Proceedings of the National Academy of Sciences.

Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing

D. Donoho, Adel Javanmard, A. Montanari, 2013, IEEE Transactions on Information Theory.

Ridge Functions and Orthonormal Ridgelets

David L. Donoho, D. Donoho, 2001, J. Approx. Theory.

Translation- and direction-invariant denoising of 2D and 3D images: experience and algorithms

David L. Donoho, Arne Stoschek, Thomas P. Yu, 1996, Optics & Photonics.

Image Denoising Techniques - An Overview

Sudipta Roy, Chandrika Kamath, Sumit Srivastava, 2014 .

A Framework for Discrete Integral Transformations I – the Pseudo-polar Fourier Transform

D. Donoho, Y. Shkolnisky, A. Averbuch, 2022 .

High-throughput single-nucleus hybrid sequencing reveals genome-transcriptome correlations in cancer

D. Donoho, J. Kendall, Peter A. Andrews, 2023, bioRxiv.

Immunology and inflammation

D. Donoho, P. Hanawalt, M. Gazzaniga, 1996 .