| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE international conference on computer vision, 2758-2766, 2015 | 2887 | 2015 |
| Flownet: Learning optical flow with convolutional networks P Fischer, A Dosovitskiy, E Ilg, P Häusser, C Hazırbaş, V Golkov, ... arXiv preprint arXiv:1504.06852, 2015 | 565 | 2015 |
| Regularization for deep learning: A taxonomy J Kukačka, V Golkov, D Cremers arXiv preprint arXiv:1710.10686, 2017 | 258 | 2017 |
| q-Space deep learning: twelve-fold shorter and model-free diffusion MRI scans V Golkov, A Dosovitskiy, JI Sperl, MI Menzel, M Czisch, P Sämann, T Brox, ... IEEE transactions on medical imaging 35 (5), 1344-1351, 2016 | 243 | 2016 |
| Clustering with deep learning: Taxonomy and new methods E Aljalbout, V Golkov, Y Siddiqui, M Strobel, D Cremers arXiv preprint arXiv:1801.07648, 2018 | 212 | 2018 |
| Efficient deep network architectures for fast chest X-ray tuberculosis screening and visualization F Pasa, V Golkov, F Pfeiffer, D Cremers, D Pfeiffer Scientific reports 9 (1), 1-9, 2019 | 195 | 2019 |
| Associative deep clustering: Training a classification network with no labels P Haeusser, J Plapp, V Golkov, E Aljalbout, D Cremers German Conference on Pattern Recognition, 18-32, 2018 | 91 | 2018 |
| Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images V Golkov, MJ Skwark, A Golkov, A Dosovitskiy, T Brox, J Meiler, ... Advances in Neural Information Processing Systems 29, 2016 | 39 | 2016 |
| q-Space novelty detection with variational autoencoders A Vasilev, V Golkov, M Meissner, I Lipp, E Sgarlata, V Tomassini, ... Computational Diffusion MRI, 113-124, 2020 | 19 | 2020 |
| 3D deep learning for biological function prediction from physical fields V Golkov, MJ Skwark, A Mirchev, G Dikov, AR Geanes, J Mendenhall, ... 2020 International Conference on 3D Vision (3DV), 928-937, 2020 | 14 | 2020 |
| Bias and precision analysis of diffusional kurtosis imaging for different acquisition schemes T Sprenger, JI Sperl, B Fernandez, V Golkov, I Eidner, PG Sämann, ... Magnetic resonance in medicine 76 (6), 1684-1696, 2016 | 14 | 2016 |
| Model-free novelty-based diffusion MRI V Golkov, T Sprenger, J Sperl, M Menzel, M Czisch, P Samann, ... 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1233-1236, 2016 | 12 | 2016 |
| Precursor microRNA identification using deep convolutional neural networks BT Do, V Golkov, GE Gürel, D Cremers BioRxiv, 414656, 2018 | 11 | 2018 |
| Rotation-equivariant deep learning for diffusion MRI P Müller, V Golkov, V Tomassini, D Cremers arXiv preprint arXiv:2102.06942, 2021 | 7 | 2021 |
| q-Space novelty detection with variational autoencoders. arXiv A Vasilev, V Golkov, M Meissner, I Lipp, E Sgarlata, V Tomassini, ... arXiv preprint arXiv:1806.02997, 2018 | 4 | 2018 |
| q-Space deep learning for Alzheimer’s disease diagnosis: Global prediction and weakly-supervised localization V Golkov, P Swazinna, MM Schmitt, QA Khan, CMW Tax, M Serahlazau, ... Proc. 27th Annu. Meeting ISMRM 1580, 2018 | 4 | 2018 |
| Speech synthesis and control using differentiable DSP G Fabbro, V Golkov, T Kemp, D Cremers arXiv preprint arXiv:2010.15084, 2020 | 3 | 2020 |
| Negative-unlabeled learning for diffusion MRI P Swazinna, V Golkov, I Lipp, E Sgarlata, V Tomassini, DK Jones, ... Proc. Intl. Soc. Mag. Reson. Med 27, 3480, 2019 | 3 | 2019 |
| Total-variation-regularized compressed sensing reconstruction for multi-shell diffusion kurtosis imaging JI Sperl, T Sprenger, ET Tan, V Golkov, MI Menzel, CJ Hardy, L Marinelli Proc. Int. Soc. Mag. Reson. Med 22, 4465, 2014 | 3 | 2014 |
| Joint super-resolution using only one anisotropic low-resolution image per q-space coordinate V Golkov, JI Sperl, MI Menzel, T Sprenger, ET Tan, L Marinelli, CJ Hardy, ... Computational Diffusion MRI, 181-191, 2014 | 3 | 2014 |
Daniel CremersTechnical University of MunichVerified email at tum.de
