Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning

18 July 2024

Papers citing "Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning"

25 / 25 papers shown

Title
High-Dimensional Confidence Regions in Sparse MRI Frederik Hoppe Felix Krahmer C. M. Verdun Marion I. Menzel Holger Rauhut 65 5 0 18 Jul 2024
Uncertainty quantification for sparse Fourier recovery F. Hoppe Felix Krahmer C. M. Verdun Marion I. Menzel Holger Rauhut 82 7 0 30 Dec 2022
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Canberk Ekmekci Müjdat Çetin UQCV 79 12 0 02 Jul 2022
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning Martin Genzel Ingo Gühring Jan Macdonald M. März 59 27 0 14 Jun 2022
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging Anastasios Nikolas Angelopoulos Amit Kohli Stephen Bates Michael I. Jordan Jitendra Malik Thayer Alshaabi Srigokul Upadhyayula Yaniv Romano UQCV OOD 80 96 0 10 Feb 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 229 1,155 0 07 Jul 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 243 235 0 23 Mar 2021
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 54 106 0 09 Nov 2020
Learning to solve TV regularized problems with unrolled algorithms Hamza Cherkaoui Jeremias Sulam Thomas Moreau 64 12 0 19 Oct 2020
Ada-LISTA: Learned Solvers Adaptive to Varying Models Aviad Aberdam Alona Golts Michael Elad 55 40 0 23 Jan 2020
De-biasing convex regularized estimators and interval estimation in linear models Pierre C. Bellec Cun-Hui Zhang 87 20 0 26 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing V. Monga Yuelong Li Yonina C. Eldar 100 1,022 0 22 Dec 2019
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI Jure Zbontar Florian Knoll Anuroop Sriram Tullie Murrell Zhengnan Huang ... Erich Owens C. L. Zitnick M. Recht D. Sodickson Yvonne W. Lui OOD 73 847 0 21 Nov 2018
MoDL: Model Based Deep Learning Architecture for Inverse Problems H. Aggarwal M. Mani M. Jacob 143 1,022 0 07 Dec 2017
Estimating the error variance in a high-dimensional linear model Guo Yu Jacob Bien 59 39 0 06 Dec 2017
Learned Primal-dual Reconstruction J. Adler Ozan Oktem MedIm 65 753 0 20 Jul 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 836 9,345 0 06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.9K 77,341 0 18 May 2015
Confidence Intervals and Hypothesis Testing for High-Dimensional Regression Adel Javanmard Andrea Montanari 249 768 0 13 Jun 2013
High-dimensional regression with unknown variance Christophe Giraud S. Huet Nicolas Verzélen 101 63 0 26 Sep 2011
Nuclear norm penalization and optimal rates for noisy low rank matrix completion V. Koltchinskii Alexandre B. Tsybakov Karim Lounici 226 664 0 29 Nov 2010
Templates for Convex Cone Problems with Applications to Sparse Signal Recovery Stephen Becker Emmanuel J. Candès Michael C. Grant 98 681 0 10 Sep 2010
$Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls$ Minimax rates of estimation for high-dimensional linear regression over $\ell_q$ -balls Garvesh Raskutti Martin J. Wainwright Bin Yu 220 575 0 11 Oct 2009
The sparsity and bias of the Lasso selection in high-dimensional linear regression Cun-Hui Zhang Jian Huang 472 869 0 07 Aug 2008
A tutorial on conformal prediction Glenn Shafer V. Vovk 452 1,149 0 21 Jun 2007