DD
David L. Donoho
math.STstat.THcs.ITmath.ITcs.LGcs.AIstat.MLAlgorithmsastro-phstat.CO
On Valency
published · living versionsW_724c9fq5·v1 · currentpublished
Prevalence of Neural Collapse during the terminal phase of deep learning training
with Vardan Papyan, X. Y. Han
1 version
Preprints & journals
80 papers in the corpus · 1990–2026Internal Data Repetition Destroys Language Models2606.24998v1 · Jessica Chudnovsky, Joshua Kazdan, Noam Levi et al.2026 · 0 citationsarXiv
Scale Dependent Data Duplication2603.06603v1 · Joshua Kazdan, Noam Levi, Rylan Schaeffer et al.2026 · 0 citationsarXiv
"Rebuilding" Statistics in the Age of AI: A Town Hall Discussion on Culture, Infrastructure, and Training2601.17510v1 · David L. Donoho, Jian Kang, Xihong Lin et al.2026 · 0 citationsarXiv
Hybrid BAG-seq: DNA and RNA from the same single nucleus reveals interactions between genomic and transcriptomic landscapes in human tumor samples.41015771 · Li, Siran, Alexander, Joan, Kendall, Jude et al.2025 · 2 citationsGenome biology. 2025;26(1):314
Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track2506.19882v3 · Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch et al.2025 · 0 citationsarXiv
Optimal Vector Compressed Sensing Using James Stein Shrinkage2505.00326v1 · Apratim Dey, David Donoho2025 · 0 citationsarXiv
Statistics and AI - A Fireside Conversation.42311443 · Statistics Up AI Alliance, International Chinese Statistical Association (ICSA), Lin, Xihong et al.2026 · 3 citationsHarvard data science review. 2025;7(2)
Universality of the Pathway in Avoiding Model Collapse2410.22812v1 · Apratim Dey, David Donoho2024 · 0 citationsarXiv
Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World2410.16713v4 · Joshua Kazdan, Rylan Schaeffer, Apratim Dey et al.2024 · 4 citationsarXiv
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data2404.01413v2 · Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey et al.2024 · 14 citationsarXiv
Principled and interpretable alignability testing and integration of single-cell data.38416677 · Ma, Rong, Sun, Eric D, Donoho, David et al.2024 · 21 citationsProceedings of the National Academy of Sciences of the United States of America. 2024;121(10):e2313719121
DNA and RNA from the same single nucleus reveals interactions between genomic and transcriptomic landscapes in human tumor samples10.1101/2023.10.04.560973v2 · Li, S., Alexander, J., Kendall, J. et al.2023 · 4 citationsbioRxiv
Data Science at the Singularity2310.00865v1 · David Donoho2023 · 52 citationsarXiv
Is your data alignable? Principled and interpretable alignability testing and integration of single-cell data10.1101/2023.08.03.551836v1 · Ma, R., Sun, E. D., Donoho, D. et al.2023 · 0 citationsbioRxiv
Optimal Eigenvalue Shrinkage in the Semicircle Limit2210.04488v2 · David L. Donoho, Michael J. Feldman2022 · 4 citationsarXiv
NUScon: a community-driven platform for quantitative evaluation of nonuniform sampling in NMR.37905225 · Pustovalova, Yulia, Delaglio, Frank, Craft, D Levi et al.2023 · 22 citationsMagnetic resonance (Gottingen, Germany). 2021;2(2):843-861
Convex Sparse Blind Deconvolution2106.07053v1 · Qingyun Sun, David Donoho2021 · 1 citationarXiv
Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path2106.02073v4 · X.Y. Han, Vardan Papyan, David L. Donoho2021 · 28 citationsarXiv
The Impossibility Region for Detecting Sparse Mixtures using the Higher Criticism2103.03218v2 · David L. Donoho, Alon Kipnis2021 · 5 citationsarXiv
The science of deep learning.33229565 · Baraniuk, Richard, Donoho, David, Gavish, Matan2021 · 50 citationsProceedings of the National Academy of Sciences of the United States of America. 2020;117(48):30029-30032
ScreeNOT: Exact MSE-Optimal Singular Value Thresholding in Correlated Noise2009.12297v3 · David L. Donoho, Matan Gavish, Elad Romanov2020 · 27 citationsAnnals of Statistics, 2023
Prevalence of neural collapse during the terminal phase of deep learning training.32958680 · Papyan, Vardan, Han, X Y, Donoho, David L2020 · 400 citationsProceedings of the National Academy of Sciences of the United States of America. 2020;117(40):24652-24663
Higher Criticism to Compare Two Large Frequency Tables, with sensitivity to Possible Rare and Weak Differences2007.01958v5 · David L. Donoho, Alon Kipnis2020 · 15 citationsAnnals of Statistics 2022, Vol. 50, No. 3, 1447-1472
Degrees of Freedom Analysis of Unrolled Neural Networks1906.03742v1 · Morteza Mardani, Qingyun Sun, Vardan Papyan et al.2019 · 5 citationsarXiv
Ambitious Data Science Can Be Painless1901.08705v1 · Hatef Monajemi, Riccardo Murri, Eric Jonas et al.2019 · 11 citationsarXiv
Optimal Covariance Estimation for Condition Number Loss in the Spiked Model1810.07403v1 · David L. Donoho, Behrooz Ghorbani2018 · 7 citationsarXiv
Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model.30258255 · Donoho, David L, Gavish, Matan, Johnstone, Iain M2023 · 185 citationsAnnals of statistics. 2018;46(4):1742-1778
Neural Proximal Gradient Descent for Compressive Imaging1806.03963v1 · Morteza Mardani, Qingyun Sun, Shreyas Vasawanala et al.2018 · 144 citationsarXiv
Recurrent Generative Adversarial Networks for Proximal Learning and Automated Compressive Image Recovery1711.10046v1 · Morteza Mardani, Hatef Monajemi, Vardan Papyan et al.2017 · 41 citationsarXiv
Sparsity/Undersampling Tradeoffs in Anisotropic Undersampling, with Applications in MR Imaging/Spectroscopy1702.03062v3 · Hatef Monajemi, David L. Donoho2017 · 9 citationsarXiv
Incoherence of Partial-Component Sampling in multidimensional NMR1702.01830v1 · Hatef Monajemi, David L. Donoho, Jeffrey C. Hoch et al.2017 · 6 citationsarXiv
Variance Breakdown of Huber (M)-estimators: 1503.02106v1 · David L. Donoho, Andrea Montanari2015 · 9 citationsarXiv
Optimal Shrinkage of Singular Values1405.7511v3 · Matan Gavish, David L. Donoho2014 · 193 citationsarXiv
High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing1310.7320v3 · David Donoho, Andrea Montanari2013 · 200 citationsarXiv
The Optimal Hard Threshold for Singular Values is 4/sqrt(3)1305.5870v3 · Matan Gavish, David L. Donoho2013 · 704 citationsarXiv
The phase transition of matrix recovery from Gaussian measurements matches the minimax MSE of matrix denoising.23650360 · Donoho, David L, Gavish, Matan, Montanari, Andrea2013 · 57 citationsProceedings of the National Academy of Sciences of the United States of America. 2013;110(21):8405-10
Minimax risk of matrix denoising by singular value thresholding1304.2085v4 · David Donoho, Matan Gavish2013 · 122 citationsAnnals of Statistics 2014, Vol. 42, No. 6, 2413-2440
Sparsity and the Bayesian Perspective1302.2758v2 · J.-L. Starck, D.L. Donoho, M.J. Fadili et al.2013 · 23 citationsarXiv
Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices.23277588 · Monajemi, Hatef, Jafarpour, Sina, Gavish, Matan et al.2013 · 100 citationsProceedings of the National Academy of Sciences of the United States of America. 2013;110(4):1181-6
Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising1111.1041v2 · David Donoho, Iain Johnstone, Andrea Montanari2011 · 178 citationsarXiv
Compressed Sensing over -balls: Minimax Mean Square Error1103.1943v2 · David Donoho, Iain Johnstone, Arian Maleki et al.2011 · 12 citationsarXiv
An invitation to reproducible computational research.20538873 · Donoho, David L2010 · 162 citationsBiostatistics (Oxford, England). 2010;11(3):385-8
Microlocal Analysis of the Geometric Separation Problem1004.3006v1 · David L. Donoho, Gitta Kutyniok2010 · 104 citationsarXiv
The Noise-Sensitivity Phase Transition in Compressed Sensing1004.1218v1 · David L. Donoho, Arian Maleki, Andrea Montanari2010 · 344 citationsarXiv
Message Passing Algorithms for Compressed Sensing: I. Motivation and Construction0911.4219v1 · David L. Donoho, Arian Maleki, Andrea Montanari2009 · 551 citationsarXiv
Message Passing Algorithms for Compressed Sensing: II. Analysis and Validation0911.4222v1 · David L. Donoho, Arian Maleki, Andrea Montanari2009 · 132 citationsarXiv
Observed universality of phase transitions in high-dimensional geometry, with implications for modern data analysis and signal processing.19805445 · Donoho, David, Tanner, Jared2010 · 439 citationsPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences. 2009;367(1906):4273-93
Feature selection by higher criticism thresholding achieves the optimal phase diagram.19805453 · Donoho, David, Jin, Jiashun2010 · 70 citationsPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences. 2009;367(1906):4449-70
Message-passing algorithms for compressed sensing.19858495 · Donoho, David L, Maleki, Arian, Montanari, Andrea2010 · 2,423 citationsProceedings of the National Academy of Sciences of the United States of America. 2009;106(45):18914-9
Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing0909.0777v1 · Arian Maleki, David L. Donoho2009 · 289 citationsarXiv
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