| Going deeper with convolutions C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 50352 | 2015 |
| Ssd: Single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 29705 | 2016 |
| Generative Adversarial Text-to-Image Synthesis S Reed, Z Akata, X Yan, L Logeswaran, B Schiele, H Lee Proceedings of The 33rd International Conference on Machine Learning, 2016 | 3181 | 2016 |
| Evaluation of Output Embeddings for Fine-Grained Image Classification Z Akata, S Reed, D Walter, H Lee, B Schiele IEEE Computer Vision and Pattern Recognition, 2015 | 1059 | 2015 |
| Training Deep Neural Networks on Noisy Labels with Bootstrapping S Reed, H Lee, D Anguelov, C Szegedy, D Erhan, A Rabinovich ArXiv e-prints, 2015 | 966 | 2015 |
| Learning Deep Representations of Fine-grained Visual Descriptions S Reed, Z Akata, B Schiele, H Lee IEEE Computer Vision and Pattern Recognition, 2016 | 837 | 2016 |
| Learning what and where to draw SE Reed, Z Akata, S Mohan, S Tenka, B Schiele, H Lee Advances in neural information processing systems 29, 2016 | 729 | 2016 |
| European conference on computer vision W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg Face detection with end-to-end integration of a convnet and a 3d model, 2016 | 652 | 2016 |
| Scalable, High-Quality Object Detection C Szegedy, S Reed, D Erhan, D Anguelov ArXiv e-prints, 2014 | 510 | 2014 |
| Neural Programmer-Interpreters S Reed, N de Freitas International Conference on Learning Representations, 2016 | 497 | 2016 |
| Weakly-supervised disentangling with recurrent transformations for 3d view synthesis J Yang, SE Reed, MH Yang, H Lee Advances in neural information processing systems 28, 2015 | 348 | 2015 |
| Deep visual analogy-making SE Reed, Y Zhang, Y Zhang, H Lee Advances in neural information processing systems 28, 2015 | 313 | 2015 |
| Learning to Disentangle Factors of Variation with Manifold Interaction S Reed, K Sohn, Y Zhang, H Lee Proceedings of the 31st International Conference on Machine Learning …, 2014 | 271 | 2014 |
| A generalist agent S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ... arXiv preprint arXiv:2205.06175, 2022 | 267 | 2022 |
| Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans A Dai, D Ritchie, M Bokeloh, S Reed, J Sturm, M Nießner Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 265 | 2018 |
| Going deeper with convolutions. arXiv 2014 C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, ... arXiv preprint arXiv:1409.4842 12, 2015 | 222 | 2015 |
| Robust imitation of diverse behaviors Z Wang, JS Merel, SE Reed, N de Freitas, G Wayne, N Heess Advances in Neural Information Processing Systems 30, 2017 | 217 | 2017 |
| Parallel multiscale autoregressive density estimation S Reed, A Oord, N Kalchbrenner, SG Colmenarejo, Z Wang, Y Chen, ... International Conference on Machine Learning, 2912-2921, 2017 | 215 | 2017 |
| Neural arithmetic logic units A Trask, F Hill, SE Reed, J Rae, C Dyer, P Blunsom Advances in neural information processing systems 31, 2018 | 194 | 2018 |
| Critic regularized regression Z Wang, A Novikov, K Zolna, JS Merel, JT Springenberg, SE Reed, ... Advances in Neural Information Processing Systems 33, 7768-7778, 2020 | 180 | 2020 |
Dragomir AnguelovDistinguished Researcher, WaymoVerified email at cs.stanford.edu
