| Informer: Beyond efficient transformer for long sequence time-series forecasting H Zhou, S Zhang, J Peng, S Zhang, J Li, H Xiong, W Zhang Proceedings of the AAAI conference on artificial intelligence 35 (12), 11106 …, 2021 | 816 | 2021 |
| COVID-CT-Dataset: a CT scan dataset about COVID-19 X Yang, X He, J Zhao, Y Zhang, S Zhang, P Xie arXiv preprint arXiv:2003.13865, 2020 | 769* | 2020 |
| Adversarial multiple source domain adaptation H Zhao*, S Zhang*, G Wu, JMF Moura, JP Costeira, GJ Gordon Advances in neural information processing systems 31, 8559-8570, 2018 | 406 | 2018 |
| Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans X He*, X Yang*, S Zhang*, J Zhao, Y Zhang, E Xing, P Xie medRxiv, 2020 | 338 | 2020 |
| FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras S Zhang*, G Wu*, JP Costeira, JMF Moura International Conference on Computer Vision (ICCV), 2017 | 208 | 2017 |
| Topology adaptive graph convolutional networks J Du, S Zhang, G Wu, JMF Moura, S Kar arXiv:1710.10370, 2017 | 187 | 2017 |
| Universal Self-Training for Unsupervised Domain Adaptation K Mei, C Zhu, J Zou, S Zhang European Conference on Computer Vision (ECCV), 2020 | 160* | 2020 |
| Understanding Traffic Density from Large-Scale Web Camera Data S Zhang, G Wu, JP Costeira, JMF Moura IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 140 | 2017 |
| Multi-source Distilling Domain Adaptation S Zhao*, G Wang*, S Zhang*, Y Gu, Y Li, Z Song, P Xu, R Hu, H Chai, ... Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020 | 133 | 2020 |
| A review of single-source deep unsupervised visual domain adaptation S Zhao, X Yue*, S Zhang*, B Li, H Zhao, B Wu, R Krishna, JE Gonzalez, ... IEEE Transactions on Neural Networks and Learning Systems, 2020 | 121 | 2020 |
| Deep Reinforcement Learning H Dong, Z Ding, S Zhang Springer Singapore, 2020 | 116 | 2020 |
| A Deep Learning Approach to IoT Authentication R Das, A Gadre, S Zhang, S Kumar, J Moura IEEE ICC 2018 Communication and Information Systems Security Symposium, 2018 | 89 | 2018 |
| Dual adversarial semantics-consistent network for generalized zero-shot learning J Ni, S Zhang, H Xie Advances in Neural Information Processing Systems 32, 2019 | 67 | 2019 |
| Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation X Yue, Z Zheng, S Zhang, Y Gao, T Darrell, K Keutzer, AS Vincentelli CVPR 2021, 2021 | 64 | 2021 |
| Self-supervised pretraining improves self-supervised pretraining CJ Reed, X Yue, A Nrusimha, S Ebrahimi, V Vijaykumar, R Mao, B Li, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 49 | 2022 |
| Multiple source domain adaptation with adversarial learning H Zhao, S Zhang, G Wu, GJ Gordon | 49 | 2018 |
| Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation B Li#, Y Wang#, S Zhang#, D Li, T Darrell, K Keutzer, H Zhao CVPR 2021, 2021 | 47 | 2021 |
| Macow: Masked convolutional generative flow X Ma, X Kong, S Zhang, E Hovy arXiv preprint arXiv:1902.04208, 2019 | 43 | 2019 |
| Differentiable spike: Rethinking gradient-descent for training spiking neural networks Y Li, Y Guo, S Zhang, S Deng, Y Hai, S Gu Advances in Neural Information Processing Systems 34, 23426-23439, 2021 | 42 | 2021 |
| Multiple source domain adaptation with adversarial training of neural networks H Zhao, S Zhang, G Wu, JP Costeira, JMF Moura, GJ Gordon arXiv preprint arXiv:1705.09684, 2017 | 41 | 2017 |
Jose M. F. MouraPhilip L. and Marsha Dowd University Professor, Carnegie Mellon Universityece.cmu.edu의 이메일 확인됨
