| Robust chemical preservation of digital information on DNA in silica with error‐correcting codes RN Grass, R Heckel, M Puddu, D Paunescu, WJ Stark Angewandte Chemie International Edition 54 (8), 2552-2555, 2015 | 741 | 2015 |
| DiffuserCam: lensless single-exposure 3D imaging N Antipa, G Kuo, R Heckel, B Mildenhall, E Bostan, R Ng, L Waller Optica 5 (1), 1-9, 2017 | 608 | 2017 |
| Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks R Heckel, P Hand International Conference on Learning Representations (ICLR), 2019 | 351 | 2019 |
| A characterization of the DNA data storage channel R Heckel, G Mikutis, RN Grass Scientific reports 9 (1), 9663, 2019 | 293 | 2019 |
| Robust subspace clustering via thresholding R Heckel, H Bölcskei IEEE Transactions on Information Theory 61 (11), 6320-6342, 2015 | 169 | 2015 |
| Deep phase decoder: self-calibrating phase microscopy with an untrained deep neural network E Bostan, R Heckel, M Chen, M Kellman, L Waller Optica 7 (6), 559-562, 2020 | 153 | 2020 |
| Accelerated MRI with un-trained neural networks MZ Darestani, R Heckel IEEE Transactions on Computational Imaging 7, 724-733, 2021 | 144 | 2021 |
| Active Ranking from Pairwise Comparisons and when Parametric Assumptions Don't Help R Heckel, NB Shah, K Ramchandran, MJ Wainwright The Annals of Statistics, 2019 | 142* | 2019 |
| Reading and writing digital data in DNA LC Meiser, PL Antkowiak, J Koch, WD Chen, AX Kohll, WJ Stark, ... Nature protocols 15 (1), 86-101, 2020 | 141 | 2020 |
| Fundamental Limits of DNA Storage Systems R Heckel, I Shomorony, K Ramchandran, DNC Tse IEEE International Symposium on Information Theory (ISIT), 2017 | 137 | 2017 |
| Low cost DNA data storage using photolithographic synthesis and advanced information reconstruction and error correction PL Antkowiak, J Lietard, MZ Darestani, MM Somoza, WJ Stark, R Heckel, ... Nature communications 11 (1), 5345, 2020 | 124 | 2020 |
| Emerging approaches to DNA data storage: challenges and prospects A Doricchi, CM Platnich, A Gimpel, F Horn, M Earle, G Lanzavecchia, ... ACS nano 16 (11), 17552-17571, 2022 | 112 | 2022 |
| Unsupervised learning with Stein's unbiased risk estimator CA Metzler, A Mousavi, R Heckel, RG Baraniuk arXiv preprint arXiv:1805.10531, 2018 | 107 | 2018 |
| Super-resolution radar R Heckel, VI Morgenshtern, M Soltanolkotabi Information and Inference: A Journal of the IMA 5 (1), 22-75, 2016 | 106 | 2016 |
| Combining data longevity with high storage capacity—layer‐by‐layer DNA encapsulated in magnetic nanoparticles WD Chen, AX Kohll, BH Nguyen, J Koch, R Heckel, WJ Stark, L Ceze, ... Advanced Functional Materials 29 (28), 1901672, 2019 | 102 | 2019 |
| Measuring Robustness in Deep Learning Based Compressive Sensing M Zalbagi Darestani, A Chaudhari, R Heckel International Conference on Machine Learning (ICML), 2021 | 98* | 2021 |
| Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators R Heckel, M Soltanolkotabi International Conference on Learning Representations (ICLR), 2020 | 91 | 2020 |
| Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximation R Heckel, M Soltanolkotabi International Conference on Machine Learning (ICML), 2020 | 88 | 2020 |
| Scalable and interpretable product recommendations via overlapping co-clustering R Heckel, M Vlachos, T Parnell, C Dünner IEEE International Conference on Data Engineering (ICDE), 1033-1044, 2017 | 85 | 2017 |
| Super-resolution radar imaging via convex optimization R Heckel Chapter in: Compressed Sensing in Radar Signal Processing, 193, 2019 | 77* | 2019 |
Robert GrassETH ZurichVerified email at chem.ethz.ch
