| Deep learning with topological signatures C Hofer, R Kwitt, M Niethammer, A Uhl arXiv preprint arXiv:1707.04041, 2017 | 113 | 2017 |
| Connectivity-optimized representation learning via persistent homology C Hofer, R Kwitt, M Niethammer, M Dixit International Conference on Machine Learning, 2751-2760, 2019 | 20 | 2019 |
| Learning Representations of Persistence Barcodes. CD Hofer, R Kwitt, M Niethammer Journal of Machine Learning Research 20 (126), 1-45, 2019 | 14 | 2019 |
| Graph filtration learning C Hofer, F Graf, B Rieck, M Niethammer, R Kwitt International Conference on Machine Learning, 4314-4323, 2020 | 8 | 2020 |
| Simple domain adaptation for cross-dataset analyses of brain MRI data C Hofer, R Kwitt, Y Höller, E Trinka, A Uhl 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 7 | 2017 |
| Factors affecting volume changes of the somatosensory cortex in patients with spinal cord injury: to be considered for future neuroprosthetic design Y Höller, A Tadzic, AC Thomschewski, P Höller, S Leis, SO Tomasi, ... Frontiers in neurology 8, 662, 2017 | 6 | 2017 |
| Tumor markers and immunomodulator substances in ascites--their value as screening and diagnosis parameters N Satz, HI Joller-Jemelka, PJ Grob, C Hofer, E Schmid, M Knoblauch Schweizerische medizinische Wochenschrift 119 (21), 762-765, 1989 | 5 | 1989 |
| Constructing shape spaces from a topological perspective C Hofer, R Kwitt, M Niethammer, Y Höller, E Trinka, A Uhl International Conference on Information Processing in Medical Imaging, 106-118, 2017 | 3 | 2017 |
| Topologically Densified Distributions C Hofer, F Graf, M Niethammer, R Kwitt International Conference on Machine Learning, 4304-4313, 2020 | 1 | 2020 |
| Dissecting Supervised Constrastive Learning F Graf, CD Hofer, M Niethammer, R Kwitt arXiv preprint arXiv:2102.08817, 2021 | | 2021 |
| Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology Y Höller, KHG Butz, AC Thomschewski, EV Schmid, CD Hofer, A Uhl, ... Computational intelligence and neuroscience 2020, 2020 | | 2020 |
| An empirical assessment of appearance descriptors applied to MRI for automated diagnosis of TLE and MCI C Hofer, R Kwitt, Y Höller, E Trinka, A Uhl Computers in biology and medicine 117, 103592, 2020 | | 2020 |
| Connectivity-Optimized Representation Learning via Persistent Homology–Supplementary material– CD Hofer, R Kwitt, M Dixit, M Niethammer | | |
Roland KwittProfessor, Department of Computer Science, University of Salzburg, AustriaBestätigte E-Mail-Adresse bei sbg.ac.at
