Reinhard Heckel

133 papers A* 17A 5B 9Misc 6Journal 88Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Asymmetric Prompt Weighting for Reinforcement Learning with Verifiable Rewards. CoRR Reinhard Heckel, Mahdi Soltanolkotabi, Christos Thramboulidis
2026	J	`jnl`	Near Optimal Code Construction for the Adversarial Torn Paper Channel With Edit Errors. CoRR Maria Abu Sini, Reinhard Heckel
2026	J	`jnl`	Test-time RL alignment exposes task familiarity artifacts in LLM benchmarks. CoRR Kun Wang, Reinhard Heckel
2025	J	`jnl`	Approximating positive homogeneous functions with scale invariant neural networks. J. Approx. Theory Stefan Bamberger, Reinhard Heckel, Felix Krahmer
2025	A*	`conf`	Efficient Noise Calculation in Deep Learning-based MRI Reconstructions. ICML Onat Dalmaz, Arjun D. Desai, Reinhard Heckel, Tolga Çukur, Akshay S. Chaudhari, Brian A. Hargreaves
2025	J	`jnl`	Efficient Noise Calculation in Deep Learning-based MRI Reconstructions. CoRR Onat Dalmaz, Arjun D. Desai, Reinhard Heckel, Tolga Çukur, Akshay S. Chaudhari, Brian A. Hargreaves
2025	—	`conf`	GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration. IEEECONF Youssef Mansour, Reinhard Heckel
2025	J	`jnl`	LLM-Guided Search for Deletion-Correcting Codes. CoRR Franziska Weindel, Reinhard Heckel
2025	B	`conf`	Near Optimal Code Construction for the Adversarial Torn Paper Channel with Edit Errors. ISIT Maria Abu Sini, Reinhard Heckel
2025	J	`jnl`	OpenThoughts: Data Recipes for Reasoning Models. CoRR Etash Kumar Guha, Ryan Marten, Sedrick Keh, Negin Raoof, Georgios Smyrnis, Hritik Bansal, Marianna Nezhurina, Jean Mercat, Trung Vu, Zayne Sprague, Ashima Suvarna, Benjamin Feuer, Liangyu Chen, Zaid Khan, Eric Frankel, Sachin Grover, Caroline Choi, Niklas Muennighoff, Shiye Su, Wanjia Zhao, John Yang, Shreyas Pimpalgaonkar, Kartik Sharma, Charlie Cheng-Jie Ji, Yichuan Deng, Sarah M. Pratt, Vivek Ramanujan, Jon Saad-Falcon, Jeffrey Li, Achal Dave, Alon Albalak, Kushal Arora, Blake Wulfe, Chinmay Hegde, Greg Durrett, Sewoong Oh, Mohit Bansal, Saadia Gabriel, Aditya Grover, Kai-Wei Chang, Vaishaal Shankar, Aaron Gokaslan, Mike A. Merrill, Tatsunori Hashimoto, Yejin Choi, Jenia Jitsev, Reinhard Heckel, Maheswaran Sathiamoorthy, Alexandros G. Dimakis, Ludwig Schmidt
2025	J	`jnl`	Trace Reconstruction with Language Models. CoRR Franziska Weindel, Michael Girsch, Reinhard Heckel
2025	B	`conf`	Transformer-Based Decoding in Concatenated Coding Schemes Under Synchronization Errors. ISIT Julian Streit, Franziska Weindel, Reinhard Heckel
2025	J	`jnl`	Transformer-Based Decoding in Concatenated Coding Schemes Under Synchronization Errors. CoRR Julian Streit, Franziska Weindel, Reinhard Heckel
2024	A*	`conf`	DataComp-LM: In search of the next generation of training sets for language models. NeurIPS Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. 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, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
2024	J	`jnl`	DataComp-LM: In search of the next generation of training sets for language models. CoRR 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 F. 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
2024	J	`jnl`	Deep Learning for Accelerated and Robust MRI Reconstruction: a Review. CoRR Reinhard Heckel, Mathews Jacob, Akshay Chaudhari, Or Perlman, Efrat Shimron
2024	J	`jnl`	GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration. CoRR Youssef Mansour, Reinhard Heckel
2024	A	`conf`	IR-FRestormer: Iterative Refinement with Fourier-Based Restormer for Accelerated MRI Reconstruction. WACV Mohammad Zalbagi Darestani, Vishwesh Nath, Wenqi Li, Yufan He, Holger R. Roth, Ziyue Xu, Daguang Xu, Reinhard Heckel, Can Zhao
2024	J	`jnl`	Implicit Neural Networks With Fourier-Feature Inputs for Free-Breathing Cardiac MRI Reconstruction. IEEE Trans. Computational Imaging Johannes F. Kunz, Stefan Ruschke, Reinhard Heckel
2024	J	`jnl`	Language models scale reliably with over-training and on downstream tasks. CoRR 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
2024	J	`jnl`	Measuring Bias of Web-filtered Text Datasets and Bias Propagation Through Training. CoRR Youssef Mansour, Reinhard Heckel
2024	J	`jnl`	Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization. J. Mach. Learn. Res. Daniel LeJeune, Jiayu Liu, Reinhard Heckel
2024	A*	`conf`	MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI. NeurIPS Tobit Klug, Kun Wang, Stefan Ruschke, Reinhard Heckel
2024	J	`jnl`	MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI. CoRR Tobit Klug, Kun Wang, Stefan Ruschke, Reinhard Heckel
2024	J	`jnl`	Resolution-Robust 3D MRI Reconstruction with 2D Diffusion Priors: Diverse-Resolution Training Outperforms Interpolation. CoRR Anselm Krainovic, Stefan Ruschke, Reinhard Heckel
2024	A*	`conf`	Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data. ICML Kang Lin, Reinhard Heckel
2024	—	`conf`	TTT-MIM: Test-Time Training with Masked Image Modeling for Denoising Distribution Shifts. ECCV (12) Youssef Mansour, Xuyang Zhong, Serdar I. Caglar, Reinhard Heckel
2023	J	`jnl`	A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography. CoRR Simon Wiedemann, Reinhard Heckel
2023	A*	`conf`	Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods. NeurIPS Tobit Klug, Dogukan Atik, Reinhard Heckel
2023	J	`jnl`	Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods. CoRR Tobit Klug, Dogukan Atik, Reinhard Heckel
2023	J	`jnl`	Approximating Positive Homogeneous Functions with Scale Invariant Neural Networks. CoRR Stefan Bamberger, Reinhard Heckel, Felix Krahmer
2023	J	`jnl`	Embracing Errors is More Efficient than Avoiding Them through Constrained Coding for DNA Data Storage. CoRR Franziska Weindel, Andreas L. Gimpel, Robert N. Grass, Reinhard Heckel
2023	—	`conf`	Embracing errors is more effective than avoiding them through constrained coding for DNA data storage. Allerton Franziska Weindel, Andreas L. Gimpel, Robert N. Grass, Reinhard Heckel
2023	J	`jnl`	Implicit Neural Networks with Fourier-Feature Inputs for Free-breathing Cardiac MRI Reconstruction. CoRR Johannes F. Kunz, Stefan Ruschke, Reinhard Heckel
2023	J	`jnl`	K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets. CoRR Frédéric Wang, Han Qi, Alfredo De Goyeneche, Reinhard Heckel, Michael Lustig, Efrat Shimron
2023	A*	`conf`	Learning Provably Robust Estimators for Inverse Problems via Jittering. NeurIPS Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel
2023	J	`jnl`	Learning Provably Robust Estimators for Inverse Problems via Jittering. CoRR Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel
2023	J	`jnl`	Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data. CoRR Kang Lin, Reinhard Heckel
2023	A*	`conf`	Scaling Laws For Deep Learning Based Image Reconstruction. ICLR Tobit Klug, Reinhard Heckel
2023	A*	`conf`	Zero-Shot Noise2Noise: Efficient Image Denoising without any Data. CVPR Youssef Mansour, Reinhard Heckel
2023	J	`jnl`	Zero-Shot Noise2Noise: Efficient Image Denoising without any Data. CoRR Youssef Mansour, Reinhard Heckel
2022	Misc	`conf`	Achieving the Capacity of a DNA Storage Channel with Linear Coding Schemes. CISS Kel Levick, Reinhard Heckel, Ilan Shomorony
2022	J	`jnl`	Guest Editorial. IEEE J. Sel. Areas Inf. Theory Paul Hand, Reinhard Heckel, Jonathan Scarlett
2022	J	`jnl`	Image-to-Image MLP-mixer for Image Reconstruction. CoRR Youssef Mansour, Kang Lin, Reinhard Heckel
2022	J	`jnl`	Information-Theoretic Foundations of DNA Data Storage. CoRR Ilan Shomorony, Reinhard Heckel
2022	J	`jnl`	Information-Theoretic Foundations of DNA Data Storage. Found. Trends Commun. Inf. Theory Ilan Shomorony, Reinhard Heckel
2022	J	`jnl`	Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization. CoRR Daniel LeJeune, Jiayu Liu, Reinhard Heckel
2022	A	`conf`	Provable Continual Learning via Sketched Jacobian Approximations. AISTATS Reinhard Heckel
2022	B	`conf`	Regularization-wise double descent: Why it occurs and how to eliminate it. ISIT Fatih Furkan Yilmaz, Reinhard Heckel
2022	J	`jnl`	Regularization-wise double descent: Why it occurs and how to eliminate it. CoRR Fatih Furkan Yilmaz, Reinhard Heckel
2022	J	`jnl`	Scaling Laws For Deep Learning Based Image Reconstruction. CoRR Tobit Klug, Reinhard Heckel
2022	A*	`conf`	Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing. ICML Mohammad Zalbagi Darestani, Jiayu Liu, Reinhard Heckel
2022	J	`jnl`	Test-time Recalibration of Conformal Predictors Under Distribution Shift Based on Unlabeled Examples. CoRR Fatih Furkan Yilmaz, Reinhard Heckel
2022	J	`jnl`	Theoretical Perspectives on Deep Learning Methods in Inverse Problems. CoRR Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar
2022	J	`jnl`	Theoretical Perspectives on Deep Learning Methods in Inverse Problems. IEEE J. Sel. Areas Inf. Theory Jonathan Scarlett, Reinhard Heckel, Miguel R. D. Rodrigues, Paul Hand, Yonina C. Eldar
2022	J	`jnl`	Untrained Graph Neural Networks for Denoising. IEEE Trans. Signal Process. Samuel Rey, Santiago Segarra, Reinhard Heckel, Antonio G. Marques
2022	—	`conf`	Vision Transformers Enable Fast and Robust Accelerated MRI. MIDL Kang Lin, Reinhard Heckel
2021	J	`jnl`	Accelerated MRI With Un-Trained Neural Networks. IEEE Trans. Computational Imaging Mohammad Zalbagi Darestani, Reinhard Heckel
2021	J	`jnl`	Achieving the Capacity of a DNA Storage Channel with Linear Coding Schemes. CoRR Kel Levick, Reinhard Heckel, Ilan Shomorony
2021	—	`conf`	Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. SIGMOD Conference Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava
2021	J	`jnl`	DNA-Based Storage: Models and Fundamental Limits. IEEE Trans. Inf. Theory Ilan Shomorony, Reinhard Heckel
2021	A*	`conf`	Data augmentation for deep learning based accelerated MRI reconstruction with limited data. ICML Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
2021	J	`jnl`	Data augmentation for deep learning based accelerated MRI reconstruction with limited data. CoRR Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
2021	A*	`conf`	Early Stopping in Deep Networks: Double Descent and How to Eliminate it. ICLR Reinhard Heckel, Fatih Furkan Yilmaz
2021	A*	`conf`	Interpolation can hurt robust generalization even when there is no noise. NeurIPS Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang
2021	J	`jnl`	Interpolation can hurt robust generalization even when there is no noise. CoRR Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang
2021	A*	`conf`	Measuring Robustness in Deep Learning Based Compressive Sensing. ICML Mohammad Zalbagi Darestani, Akshay S. Chaudhari, Reinhard Heckel
2021	J	`jnl`	Provable Continual Learning via Sketched Jacobian Approximations. CoRR Reinhard Heckel
2021	J	`jnl`	Untrained Graph Neural Networks for Denoising. CoRR Samuel Rey, Santiago Segarra, Reinhard Heckel, Antonio G. Marques
2020	J	`jnl`	Active Sampling Count Sketch (ASCS) for Online Sparse Estimation of a Trillion Scale Covariance Matrix. CoRR Zhenwei Dai, Aditya Desai, Reinhard Heckel, Anshumali Shrivastava
2020	J	`jnl`	Can Un-trained Neural Networks Compete with Trained Neural Networks at Image Reconstruction? CoRR Mohammad Zalbagi Darestani, Reinhard Heckel
2020	Misc	`conf`	Capacity of the Erasure Shuffling Channel. ICASSP Seiyun Shin, Reinhard Heckel, Ilan Shomorony
2020	A*	`conf`	Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation. ICML Reinhard Heckel, Mahdi Soltanolkotabi
2020	J	`jnl`	Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximation. CoRR Reinhard Heckel, Mahdi Soltanolkotabi
2020	J	`jnl`	DNA-Based Storage: Models and Fundamental Limits. CoRR Ilan Shomorony, Reinhard Heckel
2020	A*	`conf`	Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators. ICLR Reinhard Heckel, Mahdi Soltanolkotabi
2020	J	`jnl`	Early Stopping in Deep Networks: Double Descent and How to Eliminate it. CoRR Reinhard Heckel, Fatih Furkan Yilmaz
2020	J	`jnl`	Reducing the Representation Error of GAN Image Priors Using the Deep Decoder. CoRR Max Daniels, Paul Hand, Reinhard Heckel
2019	Misc	`conf`	A Fast and Robust Paradigm for Fourier Compressed Sensing Based on Coded Sampling. ICASSP Frank Ong, Reinhard Heckel, Kannan Ramchandran
2019	A	`conf`	Adaptive Estimation for Approximate AISTATS Daniel LeJeune, Reinhard Heckel, Richard G. Baraniuk
2019	J	`jnl`	Adaptive Estimation for Approximate k-Nearest-Neighbor Computations. CoRR Daniel LeJeune, Richard G. Baraniuk, Reinhard Heckel
2019	J	`jnl`	Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems. IEEE Trans. Knowl. Data Eng. Michail Vlachos, Celestine Dünner, Reinhard Heckel, Vassilios G. Vassiliadis, Thomas P. Parnell, Kubilay Atasu
2019	B	`conf`	Capacity Results for the Noisy Shuffling Channel. ISIT Ilan Shomorony, Reinhard Heckel
2019	J	`jnl`	Capacity Results for the Noisy Shuffling Channel. CoRR Ilan Shomorony, Reinhard Heckel
2019	J	`jnl`	Channel Normalization in Convolutional Neural Network avoids Vanishing Gradients. CoRR Zhenwei Dai, Reinhard Heckel
2019	—	`conf`	Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks. ICLR (Poster) Reinhard Heckel, Paul Hand
2019	J	`jnl`	Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators. CoRR Reinhard Heckel, Mahdi Soltanolkotabi
2019	J	`jnl`	Leveraging inductive bias of neural networks for learning without explicit human annotations. CoRR Fatih Furkan Yilmaz, Reinhard Heckel
2019	J	`jnl`	Regularizing linear inverse problems with convolutional neural networks. CoRR Reinhard Heckel
2018	J	`jnl`	A Characterization of the DNA Data Storage Channel. CoRR Reinhard Heckel, Gediminas Mikutis, Robert N. Grass
2018	J	`jnl`	Approximate Ranking from Pairwise Comparisons. CoRR Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright
2018	A	`conf`	Approximate ranking from pairwise comparisons. AISTATS Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright
2018	J	`jnl`	Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks. CoRR Reinhard Heckel, Paul Hand
2018	J	`jnl`	Deep Denoising: Rate-Optimal Recovery of Structured Signals with a Deep Prior. CoRR Reinhard Heckel, Wen Huang, Paul Hand, Vladislav Voroninski
2018	J	`jnl`	Generalized Line Spectral Estimation via Convex Optimization. IEEE Trans. Inf. Theory Reinhard Heckel, Mahdi Soltanolkotabi
2018	J	`jnl`	Super-resolution radar imaging via convex optimization. CoRR Reinhard Heckel
2018	J	`jnl`	Unsupervised Learning with Stein's Unbiased Risk Estimator. CoRR Christopher A. Metzler, Ali Mousavi, Reinhard Heckel, Richard G. Baraniuk
2017	J	`jnl`	DiffuserCam: Lensless Single-exposure 3D Imaging. CoRR Nick Antipa, Grace Kuo, Reinhard Heckel, Ben Mildenhall, Emrah Bostan, Ren Ng, Laura Waller
2017	J	`jnl`	Fundamental Limits of DNA Storage Systems. CoRR Reinhard Heckel, Ilan Shomorony, Kannan Ramchandran, David N. C. Tse
2017	B	`conf`	Fundamental limits of DNA storage systems. ISIT Reinhard Heckel, Ilan Shomorony, Kannan Ramchandran, David N. C. Tse
2017	A	`conf`	Private and Right-Protected Big Data Publication: An Analysis. SDM Reinhard Heckel, Michail Vlachos
2017	A*	`conf`	Scalable and Interpretable Product Recommendations via Overlapping Co-Clustering. ICDE Reinhard Heckel, Michail Vlachos, Thomas P. Parnell, Celestine Dünner
2017	A*	`conf`	The Sample Complexity of Online One-Class Collaborative Filtering. ICML Reinhard Heckel, Kannan Ramchandran
2017	J	`jnl`	The Sample Complexity of Online One-Class Collaborative Filtering. CoRR Reinhard Heckel, Kannan Ramchandran
2016	J	`jnl`	Active Ranking from Pairwise Comparisons and the Futility of Parametric Assumptions. CoRR Reinhard Heckel, Nihar B. Shah, Kannan Ramchandran, Martin J. Wainwright
2016	J	`jnl`	Generalized Line Spectral Estimation via Convex Optimization. CoRR Reinhard Heckel, Mahdi Soltanolkotabi
2016	J	`jnl`	Interpretable recommendations via overlapping co-clusters. CoRR Reinhard Heckel, Michail Vlachos
2016	J	`jnl`	Super-Resolution MIMO Radar. CoRR Reinhard Heckel
2016	B	`conf`	Super-resolution MIMO radar. ISIT Reinhard Heckel
2016	J	`jnl`	Toward interpretable predictive models in B2B recommender systems. IBM J. Res. Dev. Michail Vlachos, Vassilios G. Vassiliadis, Reinhard Heckel, Abdel Labbi
2015	J	`jnl`	Dimensionality-reduced subspace clustering. CoRR Reinhard Heckel, Michael Tschannen, Helmut Bölcskei
2015	J	`jnl`	Robust Subspace Clustering via Thresholding. IEEE Trans. Inf. Theory Reinhard Heckel, Helmut Bölcskei
2014	Misc	`conf`	Compressive nonparametric graphical model selection for time series. ICASSP Alexander Jung, Reinhard Heckel, Helmut Bölcskei, Franz Hlawatsch
2014	J	`jnl`	Neighborhood Selection for Thresholding-based Subspace Clustering. CoRR Reinhard Heckel, Eirikur Agustsson, Helmut Bölcskei
2014	Misc	`conf`	Neighborhood selection for thresholding-based subspace clustering. ICASSP Reinhard Heckel, Eirikur Agustsson, Helmut Bölcskei
2014	—	`—`	Sparse signal processing: subspace clustering and system identification. Reinhard Heckel
2014	B	`conf`	Subspace clustering of dimensionality-reduced data. ISIT Reinhard Heckel, Michael Tschannen, Helmut Bölcskei
2014	J	`jnl`	Subspace clustering of dimensionality-reduced data. CoRR Reinhard Heckel, Michael Tschannen, Helmut Bölcskei
2014	J	`jnl`	Super-Resolution Radar. CoRR Reinhard Heckel, Veniamin I. Morgenshtern, Mahdi Soltanolkotabi
2013	J	`jnl`	Harmonic analysis of Boolean networks: determinative power and perturbations. EURASIP J. Bioinform. Syst. Biol. Reinhard Heckel, Steffen Schober, Martin Bossert
2013	J	`jnl`	Identification of Sparse Linear Operators. IEEE Trans. Inf. Theory Reinhard Heckel, Helmut Bölcskei
2013	J	`jnl`	Noisy Subspace Clustering via Thresholding CoRR Reinhard Heckel, Helmut Bölcskei
2013	B	`conf`	Noisy subspace clustering via thresholding. ISIT Reinhard Heckel, Helmut Bölcskei
2013	J	`jnl`	Robust Subspace Clustering via Thresholding. CoRR Reinhard Heckel, Helmut Bölcskei
2013	J	`jnl`	Subspace Clustering via Thresholding and Spectral Clustering CoRR Reinhard Heckel, Helmut Bölcskei
2013	Misc	`conf`	Subspace clustering via thresholding and spectral clustering. ICASSP Reinhard Heckel, Helmut Bölcskei
2012	J	`jnl`	Identification of Sparse Linear Operators CoRR Reinhard Heckel, Helmut Bölcskei
2012	J	`jnl`	Joint Sparsity with Different Measurement Matrices CoRR Reinhard Heckel, Helmut Bölcskei
2012	—	`conf`	Joint sparsity with different measurement matrices. Allerton Conference Reinhard Heckel, Helmut Bölcskei
2011	J	`jnl`	Compressive Identification of Linear Operators CoRR Reinhard Heckel, Helmut Bölcskei
2011	B	`conf`	Compressive identification of linear operators. ISIT Reinhard Heckel, Helmut Bölcskei
2011	J	`jnl`	Detecting controlling nodes of boolean regulatory networks. EURASIP J. Bioinform. Syst. Biol. Steffen Schober, David Kracht, Reinhard Heckel, Martin Bossert
2011	J	`jnl`	Harmonic Analysis of Boolean Networks: Determinative Power and Perturbations CoRR Reinhard Heckel, Steffen Schober, Martin Bossert