| 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 | 2292 | 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 | 714 | 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 | 642 | 2013 |
| 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 | 595 | 2019 |
| 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 | 493 | 2021 |
| 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 | 413 | 2018 |
| 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 | 409 | 2020 |
| 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 | 400 | 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 | 391 | 2017 |
| 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 | 369 | 2019 |
| One-shot relational learning for knowledge graphs W Xiong, M Yu, S Chang, X Guo, WY Wang arXiv preprint arXiv:1808.09040, 2018 | 317 | 2018 |
| 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 | 310 | 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 | 284 | 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 | 284 | 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 | 282 | 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 | 271 | 2018 |
| Transgan: Two transformers can make one strong gan Y Jiang, S Chang, Z Wang arXiv preprint arXiv:2102.07074 1 (3), 2021 | 255 | 2021 |
| Invariant rationalization S Chang, Y Zhang, M Yu, T Jaakkola International Conference on Machine Learning, 1448-1458, 2020 | 250 | 2020 |
| 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 | 245 | 2016 |
| Few-shot text classification with distributional signatures Y Bao, M Wu, S Chang, R Barzilay arXiv preprint arXiv:1908.06039, 2019 | 225 | 2019 |
Yang ZhangMIT-IBM Watson AI Labยืนยันอีเมลแล้วที่ ibm.com