| Super-Resolution of Positive Sources: the Discrete Setup VI Morgenshtern, EJ Candes SIAM Journal on Imaging Sciences 9 (1), 412–444, 2016 | 147* | 2016 |
| Crystallization in large wireless networks VI Morgenshtern, H Bölcskei IEEE Trans. Inf. Theory 53 (10), 3319--3349, 2007 | 125 | 2007 |
| Super-resolution radar R Heckel, VI Morgenshtern, M Soltanolkotabi Information and Inference: A Journal of the IMA 5 (1), 22--75, 2016 | 106 | 2016 |
| Distributed orthogonalization in large interference relay networks VI Morgenshtern, H Bölcskei, RU Nabar IEEE Int. Symp. Inf. Theory (ISIT), 1211--1215, 2005 | 33 | 2005 |
| On the Sensitivity of Continuous-Time Noncoherent Fading Channel Capacity G Durisi, VI Morgenshtern, H Bölcskei IEEE Trans. Inf. Theory 58 (10), 6372--6391, 2012 | 26* | 2012 |
| Random matrix analysis of large relay networks VI Morgenshtern, H Bölcskei Allerton Conf. Commun., Control, and Comput., 106--112, 2006 | 25* | 2006 |
| Information theory of underspread WSSUS channels G Durisi, VI Morgenshtern, H Bölcskei, UG Schuster, S Shamai (Shitz) Wireless Communications over Rapidly Time-Varying Channels, 65--116, 2011 | 20* | 2011 |
| Super-resolution of positive sources on an arbitrarily fine grid VI Morgenshtern Journal of Fourier Analysis and Applications 28 (1), 4, 2022 | 19 | 2022 |
| Capacity Pre-Log of Noncoherent SIMO Channels via Hironaka's Theorem VI Morgenshtern, E Riegler, W Yang, G Durisi, S Lin, B Sturmfels, ... IEEE Trans. Inf. Theory 59 (7), 4213--4229, 2012 | 18 | 2012 |
| A self-trained model for cloud, shadow and snow detection in Sentinel-2 images of snow-and ice-covered regions KG Nambiar, VI Morgenshtern, P Hochreuther, T Seehaus, MH Braun Remote Sensing 14 (8), 1825, 2022 | 16 | 2022 |
| A short course on frame theory VI Morgenshtern, H Bölcskei Mathematical foundations for signal processing, communications, and …, 2017 | 14* | 2017 |
| Novel techniques for void filling in glacier elevation change data sets T Seehaus, VI Morgenshtern, F Hübner, E Bänsch, MH Braun Remote Sensing 12 (23), 3917, 2020 | 12 | 2020 |
| Noncoherent SIMO pre-log via resolution of singularities E Riegler, VI Morgenshtern, G Durisi, S Lin, B Sturmfels, H Bölcskei IEEE Int. Symp. Inf. Theory (ISIT), 2020--2024, 2011 | 9 | 2011 |
| The SIMO pre-log can be larger than the SISO pre-log VI Morgenshtern, G Durisi, H Bölcskei IEEE Int. Symp. Inf. Theory (ISIT), 320--324, 2010 | 8 | 2010 |
| Scattering Transform Based Image Clustering using Projection onto Orthogonal Complement A Villar-Corrales, VI Morgenshtern Proceedings of the 2021 Workshop on Intelligent Cross-Data Analysis and …, 2021 | 7 | 2021 |
| On the value of cooperation in interference relay networks V Morgenshtern, H Bölcskei Allerton Conf. Commun., Control, and Comput., 1939--1949, 2005 | 7 | 2005 |
| A lower bound on the noncoherent capacity pre-log for the MIMO channel with temporally correlated fading G Koliander, E Riegler, G Durisi, VI Morgenshtern, F Hlawatsch Allerton Conf. Commun., Control, and Comput., 1198--1205, 2012 | 6 | 2012 |
| Capacity pre-log of SIMO correlated block-fading channels W Yang, G Durisi, VI Morgenshtern, E Riegler Int. Symp. on Wireless Commun. Syst. (ISWCS), 869--873, 2011 | 6 | 2011 |
| On the sensitivity of noncoherent capacity to the channel model G Durisi, VI Morgenshtern, H Bölcskei IEEE Int. Symp. Inf. Theory (ISIT), 2174--2178, 2009 | 6 | 2009 |
| Fricative Phoneme Detection Using Deep Neural Networks and its Comparison to Traditional Methods M Yurt, P Kantharaju, S Disch, A Niedermeier, AN Escalante-B, ... Proc. Interspeech 2021, 51-55, 2021 | 5 | 2021 |
Helmut BölcskeiProfessor of Mathematical Information Science, ETH ZurichVerified email at ethz.ch
