Reinhard Heckel

According to our database, Reinhard Heckel authored at least 81 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Implicit Neural Networks With Fourier-Feature Inputs for Free-Breathing Cardiac MRI Reconstruction.

Johannes F. Kunz, Stefan Ruschke, Reinhard Heckel

IEEE Trans. Computational Imaging, 2024

Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization.

Daniel LeJeune, Jiayu Liu, Reinhard Heckel

J. Mach. Learn. Res., 2024

MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI.

Tobit Klug, Kun Wang, Stefan Ruschke, Reinhard Heckel

CoRR, 2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

CoRR, 2024

Deep Learning for Accelerated and Robust MRI Reconstruction: a Review.

Reinhard Heckel, Mathews Jacob, Akshay Chaudhari, Or Perlman, Efrat Shimron

CoRR, 2024

GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration.

Youssef Mansour, Reinhard Heckel

CoRR, 2024

Language models scale reliably with over-training and on downstream tasks.

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

CoRR, 2024

IR-FRestormer: Iterative Refinement with Fourier-Based Restormer for Accelerated MRI Reconstruction.

Mohammad Zalbagi Darestani, Vishwesh Nath, Wenqi Li, Yufan He, Holger R. Roth, Ziyue Xu, Daguang Xu, Reinhard Heckel, Can Zhao

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data.

Kang Lin, Reinhard Heckel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Free-breathing 2D Cartesian Cardiac MRI Datasets.

Johannes Künzel, Stefan Ruschke, Reinhard Heckel

Dataset, May, 2023

A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography.

Simon Wiedemann, Reinhard Heckel

CoRR, 2023

Embracing Errors is More Efficient than Avoiding Them through Constrained Coding for DNA Data Storage.

Franziska Weindel, Andreas L. Gimpel, Robert N. Grass, Reinhard Heckel

CoRR, 2023

K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets.

Frédéric Wang, Han Qi, Alfredo De Goyeneche, Reinhard Heckel, Michael Lustig, Efrat Shimron

CoRR, 2023

Approximating Positive Homogeneous Functions with Scale Invariant Neural Networks.

Stefan Bamberger, Reinhard Heckel, Felix Krahmer

CoRR, 2023

Learning Provably Robust Estimators for Inverse Problems via Jittering.

Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods.

Tobit Klug, Dogukan Atik, Reinhard Heckel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Scaling Laws For Deep Learning Based Image Reconstruction.

Tobit Klug, Reinhard Heckel

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Zero-Shot Noise2Noise: Efficient Image Denoising without any Data.

Youssef Mansour, Reinhard Heckel

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Embracing errors is more effective than avoiding them through constrained coding for DNA data storage.

Franziska Weindel, Andreas L. Gimpel, Robert N. Grass, Reinhard Heckel

Proceedings of the 59th Annual Allerton Conference on Communication, 2023

2022

Theoretical Perspectives on Deep Learning Methods in Inverse Problems.

Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar

IEEE J. Sel. Areas Inf. Theory, September, 2022

Guest Editorial.

Paul Hand, Reinhard Heckel, Jonathan Scarlett

IEEE J. Sel. Areas Inf. Theory, September, 2022

Untrained Graph Neural Networks for Denoising.

Samuel Rey, Santiago Segarra, Reinhard Heckel, Antonio G. Marques

IEEE Trans. Signal Process., 2022

Information-Theoretic Foundations of DNA Data Storage.

Ilan Shomorony, Reinhard Heckel

Found. Trends Commun. Inf. Theory, 2022

Test-time Recalibration of Conformal Predictors Under Distribution Shift Based on Unlabeled Examples.

Fatih Furkan Yilmaz, Reinhard Heckel

CoRR, 2022

Image-to-Image MLP-mixer for Image Reconstruction.

Youssef Mansour, Kang Lin, Reinhard Heckel

CoRR, 2022

Vision Transformers Enable Fast and Robust Accelerated MRI.

Kang Lin, Reinhard Heckel

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Regularization-wise double descent: Why it occurs and how to eliminate it.

Fatih Furkan Yilmaz, Reinhard Heckel

Proceedings of the IEEE International Symposium on Information Theory, 2022

Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing.

Mohammad Zalbagi Darestani, Jiayu Liu, Reinhard Heckel

Proceedings of the International Conference on Machine Learning, 2022

Achieving the Capacity of a DNA Storage Channel with Linear Coding Schemes.

Kel Levick, Reinhard Heckel, Ilan Shomorony

Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022

Provable Continual Learning via Sketched Jacobian Approximations.

Reinhard Heckel

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

DNA-Based Storage: Models and Fundamental Limits.

Ilan Shomorony, Reinhard Heckel

IEEE Trans. Inf. Theory, 2021

Accelerated MRI With Un-Trained Neural Networks.

Mohammad Zalbagi Darestani, Reinhard Heckel

IEEE Trans. Computational Imaging, 2021

Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix.

Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Interpolation can hurt robust generalization even when there is no noise.

Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Data augmentation for deep learning based accelerated MRI reconstruction with limited data.

Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi

Proceedings of the 38th International Conference on Machine Learning, 2021

Measuring Robustness in Deep Learning Based Compressive Sensing.

Mohammad Zalbagi Darestani, Akshay S. Chaudhari, Reinhard Heckel

Proceedings of the 38th International Conference on Machine Learning, 2021

Early Stopping in Deep Networks: Double Descent and How to Eliminate it.

Reinhard Heckel, Fatih Furkan Yilmaz

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction?

Mohammad Zalbagi Darestani, Reinhard Heckel

CoRR, 2020

Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximation.

Reinhard Heckel, Mahdi Soltanolkotabi

CoRR, 2020

Reducing the Representation Error of GAN Image Priors Using the Deep Decoder.

Max Daniels, Paul Hand, Reinhard Heckel

CoRR, 2020

Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation.

Reinhard Heckel, Mahdi Soltanolkotabi

Proceedings of the 37th International Conference on Machine Learning, 2020

Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators.

Reinhard Heckel, Mahdi Soltanolkotabi

Proceedings of the 8th International Conference on Learning Representations, 2020

Capacity of the Erasure Shuffling Channel.

Seiyun Shin, Reinhard Heckel, Ilan Shomorony

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems.

Michail Vlachos, Celestine Dünner, Reinhard Heckel, Vassilios G. Vassiliadis, Thomas P. Parnell, Kubilay Atasu

IEEE Trans. Knowl. Data Eng., 2019

Leveraging inductive bias of neural networks for learning without explicit human annotations.

Fatih Furkan Yilmaz, Reinhard Heckel

CoRR, 2019

Channel Normalization in Convolutional Neural Network avoids Vanishing Gradients.

Zhenwei Dai, Reinhard Heckel

CoRR, 2019

Regularizing linear inverse problems with convolutional neural networks.

Reinhard Heckel

CoRR, 2019

Adaptive Estimation for Approximate k-Nearest-Neighbor Computations.

Daniel LeJeune, Richard G. Baraniuk, Reinhard Heckel

CoRR, 2019

Capacity Results for the Noisy Shuffling Channel.

Ilan Shomorony, Reinhard Heckel

Proceedings of the IEEE International Symposium on Information Theory, 2019

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks.

Reinhard Heckel, Paul Hand

Proceedings of the 7th International Conference on Learning Representations, 2019

A Fast and Robust Paradigm for Fourier Compressed Sensing Based on Coded Sampling.

Frank Ong, Reinhard Heckel, Kannan Ramchandran

Proceedings of the IEEE International Conference on Acoustics, 2019

Adaptive Estimation for Approximate <i>k</i>-Nearest-Neighbor Computations.

Daniel LeJeune, Reinhard Heckel, Richard G. Baraniuk

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Generalized Line Spectral Estimation via Convex Optimization.

Reinhard Heckel, Mahdi Soltanolkotabi

IEEE Trans. Inf. Theory, 2018

Super-resolution radar imaging via convex optimization.

Reinhard Heckel

CoRR, 2018

Unsupervised Learning with Stein's Unbiased Risk Estimator.

Christopher A. Metzler, Ali Mousavi, Reinhard Heckel, Richard G. Baraniuk

CoRR, 2018

Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior.

Reinhard Heckel, Wen Huang, Paul Hand, Vladislav Voroninski

CoRR, 2018

A Characterization of the DNA Data Storage Channel.

Reinhard Heckel, Gediminas Mikutis, Robert N. Grass

CoRR, 2018

Approximate ranking from pairwise comparisons.

Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

DiffuserCam: Lensless Single-exposure 3D Imaging.

Nick Antipa, Grace Kuo, Reinhard Heckel, Ben Mildenhall, Emrah Bostan, Ren Ng, Laura Waller

CoRR, 2017

Private and Right-Protected Big Data Publication: An Analysis.

Reinhard Heckel, Michail Vlachos

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Fundamental limits of DNA storage systems.

Reinhard Heckel, Ilan Shomorony, Kannan Ramchandran, David N. C. Tse

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

The Sample Complexity of Online One-Class Collaborative Filtering.

Reinhard Heckel, Kannan Ramchandran

Proceedings of the 34th International Conference on Machine Learning, 2017

Scalable and Interpretable Product Recommendations via Overlapping Co-Clustering.

Reinhard Heckel, Michail Vlachos, Thomas P. Parnell, Celestine Dünner

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

2016

Toward interpretable predictive models in B2B recommender systems.

Michail Vlachos, Vassilios G. Vassiliadis, Reinhard Heckel, Abdel Labbi

IBM J. Res. Dev., 2016

Interpretable recommendations via overlapping co-clusters.

Reinhard Heckel, Michail Vlachos

CoRR, 2016

Active Ranking from Pairwise Comparisons and the Futility of Parametric Assumptions.

Reinhard Heckel, Nihar B. Shah, Kannan Ramchandran, Martin J. Wainwright

CoRR, 2016

Super-resolution MIMO radar.

Reinhard Heckel

Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

Robust Subspace Clustering via Thresholding.

Reinhard Heckel, Helmut Bölcskei

IEEE Trans. Inf. Theory, 2015

Dimensionality-reduced subspace clustering.

Reinhard Heckel, Michael Tschannen, Helmut Bölcskei

CoRR, 2015

2014

Sparse signal processing: subspace clustering and system identification.

Reinhard Heckel

PhD thesis, 2014

Super-Resolution Radar.

Reinhard Heckel, Veniamin I. Morgenshtern, Mahdi Soltanolkotabi

CoRR, 2014

Subspace clustering of dimensionality-reduced data.

Reinhard Heckel, Michael Tschannen, Helmut Bölcskei

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Compressive nonparametric graphical model selection for time series.

Alexander Jung, Reinhard Heckel, Helmut Bölcskei, Franz Hlawatsch

Proceedings of the IEEE International Conference on Acoustics, 2014

Neighborhood selection for thresholding-based subspace clustering.

Reinhard Heckel, Eirikur Agustsson, Helmut Bölcskei

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Identification of Sparse Linear Operators.

Reinhard Heckel, Helmut Bölcskei

IEEE Trans. Inf. Theory, 2013

Harmonic analysis of Boolean networks: determinative power and perturbations.

Reinhard Heckel, Steffen Schober, Martin Bossert

EURASIP J. Bioinform. Syst. Biol., 2013

Noisy subspace clustering via thresholding.

Reinhard Heckel, Helmut Bölcskei

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Subspace clustering via thresholding and spectral clustering.

Reinhard Heckel, Helmut Bölcskei

Proceedings of the IEEE International Conference on Acoustics, 2013

2012

Joint sparsity with different measurement matrices.

Reinhard Heckel, Helmut Bölcskei

Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011

Detecting controlling nodes of boolean regulatory networks.

Steffen Schober, David Kracht, Reinhard Heckel, Martin Bossert

EURASIP J. Bioinform. Syst. Biol., 2011

Compressive identification of linear operators.

Reinhard Heckel, Helmut Bölcskei

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011