| Group Equivariant Convolutional Networks TS Cohen, M Welling Proceedings of the International Conference on Machine Learning (ICML), 2016 | 2428 | 2016 |
| Geometric deep learning: Grids, groups, graphs, geodesics, and gauges MM Bronstein, J Bruna, T Cohen, P Veličković arXiv preprint arXiv:2104.13478, 2021 | 1531 | 2021 |
| Spherical CNNs TS Cohen, M Geiger, J Koehler, M Welling International Conference on Learning Representations, 2018 | 1278 | 2018 |
| Visualizing deep neural network decisions: Prediction difference analysis LM Zintgraf, TS Cohen, T Adel, M Welling arXiv preprint arXiv:1702.04595, 2017 | 918 | 2017 |
| Rotation equivariant CNNs for digital pathology BS Veeling, J Linmans, J Winkens, T Cohen, M Welling Medical image computing and computer assisted intervention–mICCAI 2018: 21st …, 2018 | 684 | 2018 |
| Steerable CNNs TS Cohen, M Welling International Conference on Learning Representations, 2017 | 601 | 2017 |
| 3d steerable cnns: Learning rotationally equivariant features in volumetric data M Weiler, M Geiger, M Welling, W Boomsma, TS Cohen Advances in Neural information processing systems 31, 2018 | 595 | 2018 |
| Gauge equivariant convolutional networks and the icosahedral CNN T Cohen, M Weiler, B Kicanaoglu, M Welling International conference on Machine learning, 1321-1330, 2019 | 501 | 2019 |
| Teacher–student curriculum learning T Matiisen, A Oliver, T Cohen, J Schulman IEEE transactions on neural networks and learning systems 31 (9), 3732-3740, 2019 | 483 | 2019 |
| A general theory of equivariant cnns on homogeneous spaces TS Cohen, M Geiger, M Weiler Advances in neural information processing systems 32, 2019 | 394 | 2019 |
| Video compression with rate-distortion autoencoders A Habibian, T Rozendaal, JM Tomczak, TS Cohen Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 265 | 2019 |
| Transformer-based transform coding Y Zhu, Y Yang, T Cohen International conference on learning representations, 2022 | 168 | 2022 |
| Weakly supervised causal representation learning J Brehmer, P De Haan, P Lippe, TS Cohen Advances in Neural Information Processing Systems 35, 38319-38331, 2022 | 149 | 2022 |
| Gauge equivariant mesh cnns: Anisotropic convolutions on geometric graphs P De Haan, M Weiler, T Cohen, M Welling arXiv preprint arXiv:2003.05425, 2020 | 139 | 2020 |
| 3D G-CNNs for pulmonary nodule detection M Winkels, TS Cohen arXiv preprint arXiv:1804.04656, 2018 | 138 | 2018 |
| Learning the Irreducible Representations of Commutative Lie Groups TS Cohen, M Welling International Conference on Machine Learning (ICML), 2014 | 134 | 2014 |
| Hexaconv E Hoogeboom, JWT Peters, TS Cohen, M Welling arXiv preprint arXiv:1803.02108, 2018 | 128 | 2018 |
| Pulmonary nodule detection in CT scans with equivariant CNNs M Winkels, TS Cohen Medical image analysis 55, 15-26, 2019 | 124 | 2019 |
| Transformation Properties of Learned Visual Representations TS Cohen, M Welling International Conference on Learning Representations (ICLR), 2015 | 122 | 2015 |
| Explorations in homeomorphic variational auto-encoding L Falorsi, P De Haan, TR Davidson, N De Cao, M Weiler, P Forré, ... arXiv preprint arXiv:1807.04689, 2018 | 116 | 2018 |
Max WellingCAIO CuspAI & Professor Machine Learning, University of Amsterdam確認したメール アドレス: uva.nl
