| Group Equivariant Convolutional Networks TS Cohen, M Welling Proceedings of the International Conference on Machine Learning (ICML), 2016 | 2913 | 2016 |
| Geometric deep learning: Grids, groups, graphs, geodesics, and gauges MM Bronstein, J Bruna, T Cohen, P Veličković arXiv preprint arXiv:2104.13478, 2021 | 2031 | 2021 |
| Spherical CNNs TS Cohen, M Geiger, J Koehler, M Welling International Conference on Learning Representations, 2018 | 1430 | 2018 |
| Visualizing deep neural network decisions: Prediction difference analysis LM Zintgraf, TS Cohen, T Adel, M Welling arXiv preprint arXiv:1702.04595, 2017 | 990 | 2017 |
| Rotation equivariant CNNs for digital pathology BS Veeling, J Linmans, J Winkens, T Cohen, M Welling International Conference on Medical image computing and computer-assisted …, 2018 | 846 | 2018 |
| 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 | 696 | 2018 |
| Steerable CNNs TS Cohen, M Welling International Conference on Learning Representations, 2017 | 693 | 2017 |
| 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 | 578 | 2019 |
| Gauge equivariant convolutional networks and the icosahedral CNN T Cohen, M Weiler, B Kicanaoglu, M Welling International conference on Machine learning, 1321-1330, 2019 | 557 | 2019 |
| A general theory of equivariant cnns on homogeneous spaces TS Cohen, M Geiger, M Weiler Advances in neural information processing systems 32, 2019 | 463 | 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 | 294 | 2019 |
| Transformer-based transform coding Y Zhu, Y Yang, T Cohen International conference on learning representations, 2022 | 264 | 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 | 211 | 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 | 159 | 2020 |
| Geometric deep learning: grids, groups, graphs, geodesics, and gauges (2021) MM Bronstein, J Bruna, T Cohen, P Velickovic arXiv preprint arXiv:2104.13478, 2021 | 158 | 2021 |
| Citris: Causal identifiability from temporal intervened sequences P Lippe, S Magliacane, S Löwe, YM Asano, T Cohen, S Gavves International Conference on Machine Learning, 13557-13603, 2022 | 153 | 2022 |
| On the expressive power of geometric graph neural networks CK Joshi, C Bodnar, SV Mathis, T Cohen, P Lio International conference on machine learning, 15330-15355, 2023 | 151 | 2023 |
| 3D G-CNNs for pulmonary nodule detection M Winkels, TS Cohen arXiv preprint arXiv:1804.04656, 2018 | 149 | 2018 |
| Learning the Irreducible Representations of Commutative Lie Groups TS Cohen, M Welling International Conference on Machine Learning (ICML), 2014 | 147 | 2014 |
| Hexaconv E Hoogeboom, JWT Peters, TS Cohen, M Welling arXiv preprint arXiv:1803.02108, 2018 | 146 | 2018 |
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
