| How to represent part-whole hierarchies in a neural network G Hinton arXiv preprint arXiv:2102.12627, 2021 | 6 | 2021 |
| Canonical Capsules: Unsupervised Capsules in Canonical Pose W Sun, A Tagliasacchi, B Deng, S Sabour, S Yazdani, G Hinton, KM Yi arXiv preprint arXiv:2012.04718, 2020 | 3 | 2020 |
| Unsupervised part representation by Flow Capsules S Sabour, A Tagliasacchi, S Yazdani, GE Hinton, DJ Fleet arXiv preprint arXiv:2011.13920, 2020 | 2 | 2020 |
| Imputer: Sequence modelling via imputation and dynamic programming W Chan, C Saharia, G Hinton, M Norouzi, N Jaitly International Conference on Machine Learning, 1403-1413, 2020 | 22 | 2020 |
| A simple framework for contrastive learning of visual representations T Chen, S Kornblith, M Norouzi, G Hinton International conference on machine learning, 1597-1607, 2020 | 1057 | 2020 |
| Teaching with Commentaries A Raghu, M Raghu, S Kornblith, D Duvenaud, G Hinton arXiv preprint arXiv:2011.03037, 2020 | 2 | 2020 |
| System and method for parallelizing convolutional neural networks A Krizhevsky, I Sutskever, GE Hinton US Patent App. 16/859,815, 2020 | | 2020 |
| Capsule neural networks GE Hinton, NMW Frosst, SSR Aghdam US Patent App. 16/652,536, 2020 | | 2020 |
| The next generation of neural networks G Hinton Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 6 | 2020 |
| Training distilled machine learning models O Vinyals, JA Dean, GE Hinton US Patent App. 16/841,859, 2020 | | 2020 |
| Big self-supervised models are strong semi-supervised learners T Chen, S Kornblith, K Swersky, M Norouzi, G Hinton arXiv preprint arXiv:2006.10029, 2020 | 177 | 2020 |
| Backpropagation and the brain TP Lillicrap, A Santoro, L Marris, CJ Akerman, G Hinton Nature Reviews Neuroscience 21 (6), 335-346, 2020 | 117 | 2020 |
| Training distilled machine learning models O Vinyals, JA Dean, GE Hinton US Patent 10,650,328, 2020 | | 2020 |
| Neural additive models: Interpretable machine learning with neural nets R Agarwal, N Frosst, X Zhang, R Caruana, GE Hinton arXiv preprint arXiv:2004.13912, 2020 | 26 | 2020 |
| Recurrent neural networks with rectified linear units QV Le, GE Hinton, N Jaitly US Patent 10,635,972, 2020 | | 2020 |
| Deflecting adversarial attacks Y Qin, N Frosst, C Raffel, G Cottrell, G Hinton arXiv preprint arXiv:2002.07405, 2020 | 6 | 2020 |
| Subclass distillation R Müller, S Kornblith, G Hinton arXiv preprint arXiv:2002.03936, 2020 | 7 | 2020 |
| Cvxnet: Learnable convex decomposition B Deng, K Genova, S Yazdani, S Bouaziz, G Hinton, A Tagliasacchi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 47 | 2020 |
| NASA: neural articulated shape approximation B Deng, JP Lewis, T Jeruzalski, G Pons-Moll, G Hinton, M Norouzi, ... arXiv preprint arXiv:1912.03207, 2019 | 31 | 2019 |
| System and method for addressing overfitting in a neural network GE Hinton, A Krizhevsky, I Sutskever, N Srivastava US Patent App. 16/523,884, 2019 | | 2019 |
Terrence SejnowskiFrancis Crick Professor, Salk Institute, Distingished Professor, UC San DiegoVerified email at salk.edu
