| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1389 | 2018 |
| Heterogeneous network embedding via deep architectures S Chang, W Han, J Tang, GJ Qi, CC Aggarwal, TS Huang Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 641 | 2015 |
| Learning locally-adaptive decision functions for person verification Z Li, S Chang, F Liang, TS Huang, L Cao, JR Smith Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 626 | 2013 |
| Transgan: Two pure transformers can make one strong gan, and that can scale up Y Jiang, S Chang, Z Wang Advances in Neural Information Processing Systems 34, 14745-14758, 2021 | 367 | 2021 |
| Autovc: Zero-shot voice style transfer with only autoencoder loss K Qian, Y Zhang, S Chang, X Yang, M Hasegawa-Johnson International Conference on Machine Learning, 5210-5219, 2019 | 342 | 2019 |
| R3: Reinforced Ranker-Reader for Open-Domain Question Answering S Wang, M Yu, X Guo, Z Wang, T Klinger, W Zhang, S Chang, G Tesauro, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 340 | 2018 |
| Jointly attentive spatial-temporal pooling networks for video-based person re-identification S Xu, Y Cheng, K Gu, Y Yang, S Chang, P Zhou Proceedings of the IEEE international conference on computer vision, 4733-4742, 2017 | 339 | 2017 |
| Dilated recurrent neural networks S Chang, Y Zhang, W Han, M Yu, X Guo, W Tan, X Cui, M Witbrock, ... Advances in neural information processing systems 30, 2017 | 282 | 2017 |
| Studying very low resolution recognition using deep networks Z Wang, S Chang, Y Yang, D Liu, TS Huang Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 245 | 2016 |
| Autogan: Neural architecture search for generative adversarial networks X Gong, S Chang, Y Jiang, Z Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 238 | 2019 |
| Diverse few-shot text classification with multiple metrics M Yu, X Guo, J Yi, S Chang, S Potdar, Y Cheng, G Tesauro, H Wang, ... arXiv preprint arXiv:1805.07513, 2018 | 232 | 2018 |
| Robust video super-resolution with learned temporal dynamics D Liu, Z Wang, Y Fan, X Liu, Z Wang, S Chang, T Huang Proceedings of the IEEE International Conference on Computer Vision, 2507-2515, 2017 | 226 | 2017 |
| The lottery ticket hypothesis for pre-trained bert networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin Advances in neural information processing systems 33, 15834-15846, 2020 | 222 | 2020 |
| Image super-resolution via dual-state recurrent networks W Han, S Chang, D Liu, M Yu, M Witbrock, TS Huang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 220 | 2018 |
| D3: Deep dual-domain based fast restoration of JPEG-compressed images Z Wang, D Liu, S Chang, Q Ling, Y Yang, TS Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 212 | 2016 |
| Adversarial robustness: From self-supervised pre-training to fine-tuning T Chen, S Liu, S Chang, Y Cheng, L Amini, Z Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 191 | 2020 |
| One-shot relational learning for knowledge graphs W Xiong, M Yu, S Chang, X Guo, WY Wang arXiv preprint arXiv:1808.09040, 2018 | 182 | 2018 |
| Evidence aggregation for answer re-ranking in open-domain question answering S Wang, M Yu, J Jiang, W Zhang, X Guo, S Chang, Z Wang, T Klinger, ... arXiv preprint arXiv:1711.05116, 2017 | 178 | 2017 |
| Negative link prediction in social media J Tang, S Chang, C Aggarwal, H Liu Proceedings of the eighth ACM international conference on web search and …, 2015 | 162 | 2015 |
| Few-shot text classification with distributional signatures Y Bao, M Wu, S Chang, R Barzilay arXiv preprint arXiv:1908.06039, 2019 | 141 | 2019 |
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