| A simple framework for contrastive learning of visual representations T Chen, S Kornblith, M Norouzi, G Hinton International Conference on Machine Learning (ICML), 1597-1607, 2020 | 23839 | 2020 |
| Big self-supervised models are strong semi-supervised learners T Chen, S Kornblith, K Swersky, M Norouzi, G Hinton Advances in Neural Information Processing Systems (NeurIPS), 2020 | 2634 | 2020 |
| Graph contrastive learning with augmentations Y You, T Chen, Y Sui, T Chen, Z Wang, Y Shen Advances in Neural Information Processing Systems (NeurIPS) 33, 5812-5823, 2020 | 2395 | 2020 |
| Big self-supervised models advance medical image classification S Azizi, B Mustafa, F Ryan, Z Beaver, J Freyberg, J Deaton, A Loh, ... International Conference on Computer Vision (ICCV), 3478-3488, 2021 | 653 | 2021 |
| SimGNN: A Neural Network Approach to Fast Graph Similarity Computation Y Bai, H Ding, S Bian, T Chen, Y Sun, W Wang International Conference on Web Search and Data Mining (WSDM), 2019 | 423 | 2019 |
| Self-Supervised GANs via Auxiliary Rotation Loss T Chen, X Zhai, M Ritter, M Lucic, N Houlsby Conference on Computer Vision and Pattern Recognition (CVPR), 12154-12163, 2019 | 375 | 2019 |
| Pix2seq: A language modeling framework for object detection T Chen, S Saxena, L Li, DJ Fleet, G Hinton International Conference on Learning Representations (ICLR), 2022 | 370 | 2022 |
| Social Influence Locality for Modeling Retweeting Behaviors. J Zhang, B Liu, J Tang, T Chen, J Li International Joint Conference on Artificial Intelligence (IJCAI), 2013 | 347 | 2013 |
| The Origins and Prevalence of Texture Bias in Convolutional Neural Networks KL Hermann, T Chen, S Kornblith Advances in Neural Information Processing Systems (NeurIPS), 2020 | 346 | 2020 |
| Self-supervised Learning for Large-scale Item Recommendations T Yao, X Yi, DZ Cheng, F Yu, T Chen, A Menon, L Hong, EH Chi, S Tjoa, ... International Conference on Information and Knowledge Management (CIKM), 2021 | 296* | 2021 |
| Analog bits: Generating discrete data using diffusion models with self-conditioning T Chen, R Zhang, G Hinton International Conference on Learning Representations (ICLR), 2022 | 262 | 2022 |
| Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification T Chen, Y Sun International Conference on Web Search and Data Mining (WSDM), 2017 | 254 | 2017 |
| Robust Pre-Training by Adversarial Contrastive Learning Z Jiang, T Chen, T Chen, Z Wang Advances in Neural Information Processing Systems (NeurIPS), 2020 | 248 | 2020 |
| On sampling strategies for neural network-based collaborative filtering T Chen, Y Sun, Y Shi, L Hong ACM International Conference on Knowledge Discovery and Data Mining (KDD …, 2017 | 247 | 2017 |
| Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ... Nature Biomedical Engineering 7 (6), 756-779, 2023 | 243* | 2023 |
| Intriguing properties of contrastive losses T Chen, C Luo, L Li Advances in Neural Information Processing Systems (NeurIPS), 2021 | 199 | 2021 |
| Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding Z Zhang, H Zhang, L Zhao, T Chen, S Arik, T Pfister AAAI Conference on Artificial Intelligence, 2022 | 187 | 2022 |
| A simple framework for contrastive learning of visual representations. arXiv 2020 T Chen, S Kornblith, M Norouzi, G Hinton arXiv preprint arXiv:2002.05709, 2023 | 177 | 2023 |
| Image augmentations for gan training Z Zhao, Z Zhang, T Chen, S Singh, H Zhang arXiv preprint arXiv:2006.02595, 2020 | 158 | 2020 |
| Decoder Denoising Pretraining for Semantic Segmentation E Brempong Asiedu, S Kornblith, T Chen, N Parmar, M Minderer, ... Transactions of Machine Learning Research, 2022 | 153* | 2022 |
Simon KornblithAnthropicE-mailová adresa ověřena na: anthropic.com