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Anzahl der Publikationen: 7
Zeitschriftenartikel
Hohenfeld, Christian; Terstiege, Ulrich; Dogan, Imis; Giunti, Paola; Parkinson, Michael H.; Mariotti, Caterina; Nanetti, Lorenzo; Fichera, Mario; Durr, Alexandra; Ewenczyk, Claire; Boesch, Sylvia; Nachbauer, Wolfgang; Klopstock, Thomas; Stendel, Claudia; de Rivera Garrido, Francisco Javier Rodriguez; Schoels, Ludger; Hayer, Stefanie N.; Klockgether, Thomas; Giordano, Ilaria; Didszun, Claire; Rai, Myriam; Pandolfo, Massimo; Rauhut, Holger 
ORCID: https://orcid.org/0000-0003-4750-5092; Schulz, Joerg B. und Reetz, Kathrin
(2022):
Prediction of the disease course in Friedreich ataxia.
In: Scientific Reports, Bd. 12, Nr. 1, 19173
[PDF, 1MB]
ORCID: https://orcid.org/0000-0003-4750-5092; Schulz, Joerg B. und Reetz, Kathrin
(2022):
Prediction of the disease course in Friedreich ataxia.
In: Scientific Reports, Bd. 12, Nr. 1, 19173
[PDF, 1MB]
Bah, Bubacarr; Rauhut, Holger ORCID: https://orcid.org/0000-0003-4750-5092; Terstiege, Ulrich und Westdickenberg, Michael
(2021):
Learning deep linear neural networks. Riemannian gradient flows and convergence to global minimizers.
In: Information and Inference, Bd. 11, Nr. 1: S. 307-353
ORCID: https://orcid.org/0000-0003-4750-5092; Terstiege, Ulrich und Westdickenberg, Michael
(2021):
Learning deep linear neural networks. Riemannian gradient flows and convergence to global minimizers.
In: Information and Inference, Bd. 11, Nr. 1: S. 307-353
Rauhut, Holger ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2019):
Low-Rank Matrix Recovery via Rank One Tight Frame Measurements.
In: Journal of Fourier Analysis and Applications, Bd. 25, Nr. 2: S. 588-593
ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2019):
Low-Rank Matrix Recovery via Rank One Tight Frame Measurements.
In: Journal of Fourier Analysis and Applications, Bd. 25, Nr. 2: S. 588-593
Kueng, Richard; Rauhut, Holger ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2017):
Low rank matrix recovery from rank one measurements.
In: Applied and Computational Harmonic Analysis, Bd. 42, Nr. 1: S. 88-116
ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2017):
Low rank matrix recovery from rank one measurements.
In: Applied and Computational Harmonic Analysis, Bd. 42, Nr. 1: S. 88-116
Kabanava, Maryia; Kueng, Richard; Rauhut, Holger ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2016):
Stable low-rank matrix recovery via null space properties.
In: Information and Inference, Bd. 5, Nr. 4: S. 405-441
ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2016):
Stable low-rank matrix recovery via null space properties.
In: Information and Inference, Bd. 5, Nr. 4: S. 405-441
Konferenzbeitrag
Kabanava, Maryia; Rauhut, Holger ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich ORCID: https://orcid.org/0000-0003-4750-5092
(2015):
On the minimal number of measurements in low-rank matrix recovery.
2015 International Conference on Sampling Theory and Applications (SampTA), Washington, DC, 25-29 May 2015.
In: 2015 International Conference on Sampling Theory and Applications (SampTA),
IEEE. S. 382-386
ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich ORCID: https://orcid.org/0000-0003-4750-5092
(2015):
On the minimal number of measurements in low-rank matrix recovery.
2015 International Conference on Sampling Theory and Applications (SampTA), Washington, DC, 25-29 May 2015.
In: 2015 International Conference on Sampling Theory and Applications (SampTA),
IEEE. S. 382-386
Kabanava, Maryia; Rauhut, Holger ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2015):
Analysis of low rank matrix recovery via Mendelson's small ball method.
International Conference on Sampling Theory and Applications (SampTA), Washington, DC, 25-29 May 2015.
In: 2015 International Conference on Sampling Theory and Applications (SampTA),
IEEE. S. 387-391
ORCID: https://orcid.org/0000-0003-4750-5092 und Terstiege, Ulrich
(2015):
Analysis of low rank matrix recovery via Mendelson's small ball method.
International Conference on Sampling Theory and Applications (SampTA), Washington, DC, 25-29 May 2015.
In: 2015 International Conference on Sampling Theory and Applications (SampTA),
IEEE. S. 387-391