| How to backdoor federated learning E Bagdasaryan, A Veit, Y Hua, D Estrin, V Shmatikov International Conference on Artificial Intelligence and Statistics, 2938-2948, 2020 | 1211 | 2020 |
| Residual networks behave like ensembles of relatively shallow networks A Veit, MJ Wilber, S Belongie Advances in neural information processing systems 29, 2016 | 1063 | 2016 |
| OpenImages: A public dataset for large-scale multi-label and multi-class image classification. I Krasin, T Duerig, N Alldrin, A Veit, S Abu-El-Haija, S Belongie, D Cai, ... Dataset available from https://github.com/openimages, 2016 | 664 | 2016 |
| Deep learning is robust to massive label noise D Rolnick, A Veit, S Belongie, N Shavit arXiv preprint arXiv:1705.10694, 2017 | 521 | 2017 |
| Learning from noisy large-scale datasets with minimal supervision A Veit, N Alldrin, G Chechik, I Krasin, A Gupta, S Belongie Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 461 | 2017 |
| Coco-text: Dataset and benchmark for text detection and recognition in natural images A Veit, T Matera, L Neumann, J Matas, S Belongie arXiv preprint arXiv:1601.07140, 2016 | 418 | 2016 |
| Convolutional Networks with Adaptive Inference Graphs A Veit, S Belongie European Conference on Computer Vision (ECCV '18), 2017 | 381 | 2017 |
| Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences A Veit*, B Kovacs*, S Bell, J McAuley, K Bala, S Belongie IEEE International Conference on Computer Vision, ICCV '15, 2015 | 326 | 2015 |
| Long-tail learning via logit adjustment AK Menon, S Jayasumana, AS Rawat, H Jain, A Veit, S Kumar arXiv preprint arXiv:2007.07314, 2020 | 325 | 2020 |
| Understanding robustness of transformers for image classification S Bhojanapalli, A Chakrabarti, D Glasner, D Li, T Unterthiner, A Veit Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 199 | 2021 |
| Why are adaptive methods good for attention models? J Zhang, SP Karimireddy, A Veit, S Kim, S Reddi, S Kumar, S Sra Advances in Neural Information Processing Systems 33, 15383-15393, 2020 | 167* | 2020 |
| Conditional Similarity Networks A Veit, S Belongie, T Karaletsos Computer Vision and Pattern Recognition, (CVPR '17), 2017 | 160 | 2017 |
| Learning to evaluate image captioning Y Cui, G Yang, A Veit, X Huang, S Belongie Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 122 | 2018 |
| Residual networks are exponential ensembles of relatively shallow networks A Veit, M Wilber, S Belongie arXiv preprint arXiv:1605.06431 1 (2), 3, 2016 | 117 | 2016 |
| Household Electricity Demand Forecasting: Benchmarking State-of-the-Art Methods A Veit, C Goebel, R Tidke, C Doblander, HA Jacobsen e-Energy '14 5th International Conference on Future Energy System, 233-234, 2014 | 101 | 2014 |
| Learning to Detect and Match Keypoints with Deep Architectures H Altwaijry, A Veit, S Belongie British Machine Vision Conference (BMVC), 2016 | 84 | 2016 |
| Icdar2017 robust reading challenge on coco-text R Gomez, B Shi, L Gomez, L Numann, A Veit, J Matas, S Belongie, ... 2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017 | 56 | 2017 |
| Multiagent Coordination for Energy Consumption Scheduling in Consumer Cooperatives. A Veit, Y Xu, R Zheng, N Chakraborty, KP Sycara 27th AAAI Conference on Artificial Intelligence, 1362-1368, 2013 | 38 | 2013 |
| Coping with label shift via distributionally robust optimisation J Zhang, A Menon, A Veit, S Bhojanapalli, S Kumar, S Sra arXiv preprint arXiv:2010.12230, 2020 | 32 | 2020 |
| Separating self-expression and visual content in hashtag supervision A Veit, M Nickel, S Belongie, L van der Maaten Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 32 | 2018 |
Serge BelongieUniversity of CopenhagenVerified email at di.ku.dk
