New and improved Johnson–Lindenstrauss embeddings via the restricted isometry property F Krahmer, R Ward SIAM Journal on Mathematical Analysis 43 (3), 1269-1281, 2011 | 336 | 2011 |
Suprema of chaos processes and the restricted isometry property F Krahmer, S Mendelson, H Rauhut Communications on Pure and Applied Mathematics 67 (11), 1877-1904, 2014 | 263 | 2014 |
Stable and robust sampling strategies for compressive imaging F Krahmer, R Ward IEEE Trans. Image Proc. 23 (2), 612-622, 2014 | 217* | 2014 |
A partial derandomization of phaselift using spherical designs D Gross, F Krahmer, R Kueng Journal of Fourier Analysis and Applications 21 (2), 229-266, 2015 | 126 | 2015 |
Improved recovery guarantees for phase retrieval from coded diffraction patterns D Gross, F Krahmer, R Kueng Applied and Computational Harmonic Analysis 42 (1), 37-64, 2017 | 120 | 2017 |
Blind image deconvolution: Motion blur estimation F Krahmer, Y Lin, B McAdoo, K Ott, J Wang, D Widemann, B Wohlberg | 116 | 2006 |
On unlimited sampling A Bhandari, F Krahmer, R Raskar 2017 International Conference on Sampling Theory and Applications (SampTA …, 2017 | 102 | 2017 |
On unlimited sampling and reconstruction A Bhandari, F Krahmer, R Raskar IEEE Transactions on Signal Processing 69, 3827-3839, 2020 | 92 | 2020 |
Quantization and compressive sensing PT Boufounos, L Jacques, F Krahmer, R Saab Compressed Sensing and its Applications: MATHEON Workshop 2013, 193-237, 2015 | 89 | 2015 |
Unlimited sampling from theory to practice: Fourier-Prony recovery and prototype ADC A Bhandari, F Krahmer, T Poskitt IEEE Transactions on Signal Processing 70, 1131-1141, 2021 | 69 | 2021 |
Optimal injectivity conditions for bilinear inverse problems with applications to identifiability of deconvolution problems M Kech, F Krahmer SIAM Journal on Applied Algebra and Geometry 1 (1), 20-37, 2017 | 66 | 2017 |
Group testing for SARS-CoV-2 allows for up to 10-fold efficiency increase across realistic scenarios and testing strategies CM Verdun, T Fuchs, P Harar, D Elbrächter, DS Fischer, J Berner, ... Frontiers in Public Health 9, 583377, 2021 | 65 | 2021 |
Unlimited sampling of sparse signals A Bhandari, F Krahmer, R Raskar 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 61 | 2018 |
A novel compressed sensing scheme for photoacoustic tomography M Sandbichler, F Krahmer, T Berer, P Burgholzer, M Haltmeier SIAM Journal on Applied Mathematics 75 (6), 2475-2494, 2015 | 59 | 2015 |
An optimal family of exponentially accurate one‐bit Sigma‐Delta quantization schemes P Deift, F Krahmer, CS Güntürk Communications on Pure and Applied Mathematics 64 (7), 883-919, 2011 | 58 | 2011 |
Uncertainty in time–frequency representations on finite Abelian groups and applications F Krahmer, GE Pfander, P Rashkov Applied and Computational Harmonic Analysis 25 (2), 209-225, 2008 | 58 | 2008 |
Optimally sparse frames PG Casazza, A Heinecke, F Krahmer, G Kutyniok IEEE transactions on information Theory 57 (11), 7279-7287, 2011 | 55 | 2011 |
Blind demixing and deconvolution at near-optimal rate P Jung, F Krahmer, D Stöger IEEE Transactions on Information Theory 64 (2), 704-727, 2017 | 50 | 2017 |
Sigma–delta quantization of sub-gaussian frame expansions and its application to compressed sensing F Krahmer, R Saab, Ö Yilmaz Information and Inference: A Journal of the IMA 3 (1), 40-58, 2014 | 49 | 2014 |
Unlimited sampling of sparse sinusoidal mixtures A Bhandari, F Krahmer, R Raskar 2018 IEEE International Symposium on Information Theory (ISIT), 336-340, 2018 | 43 | 2018 |