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Reinhard Heckel
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Publications
- 2024
- [c36]Mohammad Zalbagi Darestani, Vishwesh Nath, Wenqi Li, Yufan He, Holger R. Roth, Ziyue Xu, Daguang Xu, Reinhard Heckel, Can Zhao:
IR-FRestormer: Iterative Refinement with Fourier-Based Restormer for Accelerated MRI Reconstruction. WACV 2024: 7640-7649 - [i58]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt:
Language models scale reliably with over-training and on downstream tasks. CoRR abs/2403.08540 (2024) - 2023
- [c31]Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel:
Learning Provably Robust Estimators for Inverse Problems via Jittering. NeurIPS 2023 - [i54]Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel:
Learning Provably Robust Estimators for Inverse Problems via Jittering. CoRR abs/2307.12822 (2023) - [i52]Frédéric Wang, Han Qi, Alfredo De Goyeneche, Reinhard Heckel, Michael Lustig, Efrat Shimron:
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets. CoRR abs/2308.02958 (2023) - 2022
- [j13]Ilan Shomorony, Reinhard Heckel:
Information-Theoretic Foundations of DNA Data Storage. Found. Trends Commun. Inf. Theory 19(1): 1-106 (2022) - [j12]Paul Hand, Reinhard Heckel, Jonathan Scarlett:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 3(3): 432 (2022) - [j11]Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar:
Theoretical Perspectives on Deep Learning Methods in Inverse Problems. IEEE J. Sel. Areas Inf. Theory 3(3): 433-453 (2022) - [j10]Samuel Rey, Santiago Segarra, Reinhard Heckel, Antonio G. Marques:
Untrained Graph Neural Networks for Denoising. IEEE Trans. Signal Process. 70: 5708-5723 (2022) - [c29]Kel Levick, Reinhard Heckel, Ilan Shomorony:
Achieving the Capacity of a DNA Storage Channel with Linear Coding Schemes. CISS 2022: 218-223 - [c28]Mohammad Zalbagi Darestani, Jiayu Liu, Reinhard Heckel:
Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing. ICML 2022: 4754-4776 - [i46]Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar:
Theoretical Perspectives on Deep Learning Methods in Inverse Problems. CoRR abs/2206.14373 (2022) - [i43]Daniel LeJeune, Jiayu Liu, Reinhard Heckel:
Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization. CoRR abs/2210.11589 (2022) - [i42]Ilan Shomorony, Reinhard Heckel:
Information-Theoretic Foundations of DNA Data Storage. CoRR abs/2211.05552 (2022) - 2021
- [j9]Mohammad Zalbagi Darestani, Reinhard Heckel:
Accelerated MRI With Un-Trained Neural Networks. IEEE Trans. Computational Imaging 7: 724-733 (2021) - [j8]Ilan Shomorony, Reinhard Heckel:
DNA-Based Storage: Models and Fundamental Limits. IEEE Trans. Inf. Theory 67(6): 3675-3689 (2021) - [c24]Mohammad Zalbagi Darestani, Akshay S. Chaudhari, Reinhard Heckel:
Measuring Robustness in Deep Learning Based Compressive Sensing. ICML 2021: 2433-2444 - [c23]Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi:
Data augmentation for deep learning based accelerated MRI reconstruction with limited data. ICML 2021: 3057-3067 - [c22]Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang:
Interpolation can hurt robust generalization even when there is no noise. NeurIPS 2021: 23465-23477 - [c21]Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava:
Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. SIGMOD Conference 2021: 352-364 - [i41]Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi:
Data augmentation for deep learning based accelerated MRI reconstruction with limited data. CoRR abs/2106.14947 (2021) - [i40]Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang:
Interpolation can hurt robust generalization even when there is no noise. CoRR abs/2108.02883 (2021) - [i39]Samuel Rey, Santiago Segarra, Reinhard Heckel, Antonio G. Marques:
Untrained Graph Neural Networks for Denoising. CoRR abs/2109.11700 (2021) - [i38]Kel Levick, Reinhard Heckel, Ilan Shomorony:
Achieving the Capacity of a DNA Storage Channel with Linear Coding Schemes. CoRR abs/2112.01630 (2021) - 2020
- [c20]Seiyun Shin, Reinhard Heckel, Ilan Shomorony:
Capacity of the Erasure Shuffling Channel. ICASSP 2020: 8841-8845 - [c19]Reinhard Heckel, Mahdi Soltanolkotabi:
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators. ICLR 2020 - [c18]Reinhard Heckel, Mahdi Soltanolkotabi:
Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation. ICML 2020: 4149-4158 - [i36]Ilan Shomorony, Reinhard Heckel:
DNA-Based Storage: Models and Fundamental Limits. CoRR abs/2001.06311 (2020) - [i35]Max Daniels, Paul Hand, Reinhard Heckel:
Reducing the Representation Error of GAN Image Priors Using the Deep Decoder. CoRR abs/2001.08747 (2020) - [i34]Reinhard Heckel, Mahdi Soltanolkotabi:
Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximation. CoRR abs/2005.03991 (2020) - [i33]Mohammad Zalbagi Darestani, Reinhard Heckel:
Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction? CoRR abs/2007.02471 (2020) - [i31]Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava:
Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. CoRR abs/2010.15951 (2020) - 2019
- [c17]Daniel LeJeune, Reinhard Heckel, Richard G. Baraniuk:
Adaptive Estimation for Approximate $k$-Nearest-Neighbor Computations. AISTATS 2019: 3099-3107 - [c16]Frank Ong, Reinhard Heckel, Kannan Ramchandran:
A Fast and Robust Paradigm for Fourier Compressed Sensing Based on Coded Sampling. ICASSP 2019: 5117-5121 - [c15]Reinhard Heckel, Paul Hand:
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks. ICLR (Poster) 2019 - [c14]Ilan Shomorony, Reinhard Heckel:
Capacity Results for the Noisy Shuffling Channel. ISIT 2019: 762-766 - [i30]Daniel LeJeune, Richard G. Baraniuk, Reinhard Heckel:
Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. CoRR abs/1902.09465 (2019) - [i29]Ilan Shomorony, Reinhard Heckel:
Capacity Results for the Noisy Shuffling Channel. CoRR abs/1902.10832 (2019) - [i27]Zhenwei Dai, Reinhard Heckel:
Channel Normalization in Convolutional Neural Network avoids Vanishing Gradients. CoRR abs/1907.09539 (2019) - [i25]Reinhard Heckel, Mahdi Soltanolkotabi:
Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators. CoRR abs/1910.14634 (2019) - 2018
- [j6]Reinhard Heckel, Mahdi Soltanolkotabi:
Generalized Line Spectral Estimation via Convex Optimization. IEEE Trans. Inf. Theory 64(6): 4001-4023 (2018) - [c13]Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright:
Approximate ranking from pairwise comparisons. AISTATS 2018: 1057-1066 - [i24]Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright:
Approximate Ranking from Pairwise Comparisons. CoRR abs/1801.01253 (2018) - [i22]Reinhard Heckel, Wen Huang, Paul Hand, Vladislav Voroninski:
Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior. CoRR abs/1805.08855 (2018) - [i21]Christopher A. Metzler, Ali Mousavi, Reinhard Heckel, Richard G. Baraniuk:
Unsupervised Learning with Stein's Unbiased Risk Estimator. CoRR abs/1805.10531 (2018) - [i19]Reinhard Heckel, Paul Hand:
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks. CoRR abs/1810.03982 (2018) - 2017
- [c11]Reinhard Heckel, Kannan Ramchandran:
The Sample Complexity of Online One-Class Collaborative Filtering. ICML 2017: 1452-1460 - [c10]Reinhard Heckel, Ilan Shomorony, Kannan Ramchandran, David N. C. Tse:
Fundamental limits of DNA storage systems. ISIT 2017: 3130-3134 - [i18]Reinhard Heckel, Ilan Shomorony, Kannan Ramchandran, David N. C. Tse:
Fundamental Limits of DNA Storage Systems. CoRR abs/1705.04732 (2017) - [i17]Reinhard Heckel, Kannan Ramchandran:
The Sample Complexity of Online One-Class Collaborative Filtering. CoRR abs/1706.00061 (2017) - [i16]Nick Antipa, Grace Kuo, Reinhard Heckel, Ben Mildenhall, Emrah Bostan, Ren Ng, Laura Waller:
DiffuserCam: Lensless Single-exposure 3D Imaging. CoRR abs/1710.02134 (2017) - 2016
- [i13]Reinhard Heckel, Nihar B. Shah, Kannan Ramchandran, Martin J. Wainwright:
Active Ranking from Pairwise Comparisons and the Futility of Parametric Assumptions. CoRR abs/1606.08842 (2016) - [i12]Reinhard Heckel, Mahdi Soltanolkotabi:
Generalized Line Spectral Estimation via Convex Optimization. CoRR abs/1609.08198 (2016) - 2015
- [j4]Reinhard Heckel, Helmut Bölcskei:
Robust Subspace Clustering via Thresholding. IEEE Trans. Inf. Theory 61(11): 6320-6342 (2015) - [i11]Reinhard Heckel, Michael Tschannen, Helmut Bölcskei:
Dimensionality-reduced subspace clustering. CoRR abs/1507.07105 (2015) - 2014
- [c7]Alexander Jung, Reinhard Heckel, Helmut Bölcskei, Franz Hlawatsch:
Compressive nonparametric graphical model selection for time series. ICASSP 2014: 769-773 - [c6]Reinhard Heckel, Eirikur Agustsson, Helmut Bölcskei:
Neighborhood selection for thresholding-based subspace clustering. ICASSP 2014: 6761-6765 - [c5]Reinhard Heckel, Michael Tschannen, Helmut Bölcskei:
Subspace clustering of dimensionality-reduced data. ISIT 2014: 2997-3001 - [i10]Reinhard Heckel, Eirikur Agustsson, Helmut Bölcskei:
Neighborhood Selection for Thresholding-based Subspace Clustering. CoRR abs/1403.3438 (2014) - [i9]Reinhard Heckel, Michael Tschannen, Helmut Bölcskei:
Subspace clustering of dimensionality-reduced data. CoRR abs/1404.6818 (2014) - [i8]Reinhard Heckel, Veniamin I. Morgenshtern, Mahdi Soltanolkotabi:
Super-Resolution Radar. CoRR abs/1411.6272 (2014) - 2013
- [j2]Reinhard Heckel, Helmut Bölcskei:
Identification of Sparse Linear Operators. IEEE Trans. Inf. Theory 59(12): 7985-8000 (2013) - [c4]Reinhard Heckel, Helmut Bölcskei:
Subspace clustering via thresholding and spectral clustering. ICASSP 2013: 3263-3267 - [c3]Reinhard Heckel, Helmut Bölcskei:
Noisy subspace clustering via thresholding. ISIT 2013: 1382-1386 - [i7]Reinhard Heckel, Helmut Bölcskei:
Subspace Clustering via Thresholding and Spectral Clustering. CoRR abs/1303.3716 (2013) - [i6]Reinhard Heckel, Helmut Bölcskei:
Noisy Subspace Clustering via Thresholding. CoRR abs/1305.3486 (2013) - [i5]Reinhard Heckel, Helmut Bölcskei:
Robust Subspace Clustering via Thresholding. CoRR abs/1307.4891 (2013) - 2012
- [c2]Reinhard Heckel, Helmut Bölcskei:
Joint sparsity with different measurement matrices. Allerton Conference 2012: 698-702 - [i4]Reinhard Heckel, Helmut Bölcskei:
Identification of Sparse Linear Operators. CoRR abs/1209.5187 (2012) - [i3]Reinhard Heckel, Helmut Bölcskei:
Joint Sparsity with Different Measurement Matrices. CoRR abs/1210.2272 (2012) - 2011
- [c1]Reinhard Heckel, Helmut Bölcskei:
Compressive identification of linear operators. ISIT 2011: 1412-1416 - [i2]Reinhard Heckel, Helmut Bölcskei:
Compressive Identification of Linear Operators. CoRR abs/1105.5215 (2011)
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last updated on 2024-04-18 20:33 CEST by the dblp team
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