| Dynamic routing between capsules S Sabour, N Frosst, GE Hinton Advances in neural information processing systems 30, 2017 | 5632 | 2017 |
| Matrix capsules with EM routing S Sabour, N Frosst, G Hinton 6th international conference on learning representations, ICLR, 1-15, 2018 | 1231* | 2018 |
| Adversarial manipulation of deep representations S Sabour, Y Cao, F Faghri, DJ Fleet arXiv preprint arXiv:1511.05122, 2015 | 341 | 2015 |
| Stacked capsule autoencoders A Kosiorek, S Sabour, YW Teh, GE Hinton Advances in neural information processing systems 32, 2019 | 312 | 2019 |
| Lingvo: a modular and scalable framework for sequence-to-sequence modeling J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ... arXiv preprint arXiv:1902.08295, 2019 | 198 | 2019 |
| Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... arXiv preprint arXiv:2111.12594, 2021 | 151 | 2021 |
| Kubric: A scalable dataset generator K Greff, F Belletti, L Beyer, C Doersch, Y Du, D Duckworth, DJ Fleet, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 125 | 2022 |
| Detecting and diagnosing adversarial images with class-conditional capsule reconstructions Y Qin, N Frosst, S Sabour, C Raffel, G Cottrell, G Hinton arXiv preprint arXiv:1907.02957, 2019 | 90 | 2019 |
| Canonical capsules: Self-supervised capsules in canonical pose W Sun, A Tagliasacchi, B Deng, S Sabour, S Yazdani, GE Hinton, KM Yi Advances in Neural information processing systems 34, 24993-25005, 2021 | 77 | 2021 |
| Dynamic routing between capsules. arXiv S Sabour, N Frosst, GE Hinton arXiv preprint arXiv:1710.09829, 2017 | 59 | 2017 |
| Darccc: Detecting adversaries by reconstruction from class conditional capsules N Frosst, S Sabour, G Hinton arXiv preprint arXiv:1811.06969, 2018 | 56 | 2018 |
| Dynamic routing between capsules. arXiv 2017 S Sabour, N Frosst, GE Hinton arXiv preprint arXiv:1710.09829, 0 | 55 | |
| Optimal completion distillation for sequence learning S Sabour, W Chan, M Norouzi arXiv preprint arXiv:1810.01398, 2018 | 46 | 2018 |
| Unsupervised part representation by flow capsules S Sabour, A Tagliasacchi, S Yazdani, G Hinton, DJ Fleet International Conference on Machine Learning, 9213-9223, 2021 | 41 | 2021 |
| Robustnerf: Ignoring distractors with robust losses S Sabour, S Vora, D Duckworth, I Krasin, DJ Fleet, A Tagliasacchi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 24 | 2023 |
| nerf2nerf: Pairwise registration of neural radiance fields L Goli, D Rebain, S Sabour, A Garg, A Tagliasacchi 2023 IEEE International Conference on Robotics and Automation (ICRA), 9354-9361, 2023 | 20 | 2023 |
| Testing GLOM's ability to infer wholes from ambiguous parts L Culp, S Sabour, GE Hinton arXiv preprint arXiv:2211.16564, 2022 | 3 | 2022 |
| Kubric: A scalable dataset generator A Kundu, A Tagliasacchi, AY Mak, A Stone, C Doersch, C Oztireli, ... | 1 | 2022 |
| Evaluation of the major properties of composite resin containing zinc-oxide nano-particles M Azarsina, S Yazdani, M Jalali, S Sabour, S Kasraei Dent Adv Res 2, 121, 2017 | | 2017 |
| ADVERSARIAL MANIPULATION OF DEEP REPRESEN S Sabour, Y Cao, F Faghri, DJ Fleet arXiv preprint arXiv:1511.05122, 2015 | | 2015 |
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoDirección de correo verificada de cs.toronto.edu
