| A large-scale study of representation learning with the visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 263 | 2019 |
| The visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... | 64 | 2019 |
| Optimal stopping via randomized neural networks C Herrera, F Krach, P Ruyssen, J Teichmann arXiv preprint arXiv:2104.13669, 2021 | 35 | 2021 |
| A large-scale study of representation learning with the visual task adaptation benchmark. arXiv 2019 X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 1910 | 13 | 1910 |
| Denise: Deep learning based robust PCA for positive semidefinite matrices C Herrera, F Krach, A Kratsios, P Ruyssen, J Teichmann stat 1050 (5), 2020 | 9 | 2020 |
| Low-rank plus sparse decomposition of covariance matrices using neural network parametrization M Baes, C Herrera, A Neufeld, P Ruyssen IEEE Transactions on Neural Networks and Learning Systems 34 (1), 171-185, 2021 | 8 | 2021 |
| A large-scale study of representation learning with the visual task adaptation benchmark. arXiv X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 7 | 2019 |
| Using floorplans for software visualization ZV Apanovich, M Bulyonkov, A Bulyonkova, P Emelyanov, N Filatkina, ... Bulletin of NCC, 27-44, 2006 | 6 | 2006 |
| Denise: Deep robust principal component analysis for positive semidefinite matrices C Herrera, F Krach, A Kratsios, P Ruyssen, J Teichmann arXiv preprint arXiv:2004.13612, 2020 | 2 | 2020 |
Calypso HerreraETH ZurichVerified email at math.ethz.ch
