| Convolutional LSTM network: A machine learning approach for precipitation nowcasting X Shi, Z Chen, H Wang, DY Yeung, WK Wong, W Woo Advances in neural information processing systems 28, 2015 | 7239 | 2015 |
| Deep learning for precipitation nowcasting: A benchmark and a new model X Shi, Z Gao, L Lausen, H Wang, DY Yeung, W Wong, W Woo Advances in neural information processing systems 30, 2017 | 624 | 2017 |
| Gaan: Gated attention networks for learning on large and spatiotemporal graphs J Zhang, X Shi, J Xie, H Ma, I King, DY Yeung arXiv preprint arXiv:1803.07294, 2018 | 586 | 2018 |
| Dynamic key-value memory networks for knowledge tracing J Zhang, X Shi, I King, DY Yeung Proceedings of the 26th international conference on World Wide Web, 765-774, 2017 | 470 | 2017 |
| Spatiotemporal modeling for crowd counting in videos F Xiong, X Shi, DY Yeung Proceedings of the IEEE international conference on computer vision, 5151-5159, 2017 | 208 | 2017 |
| Gluoncv and gluonnlp: Deep learning in computer vision and natural language processing J Guo, H He, T He, L Lausen, M Li, H Lin, X Shi, C Wang, J Xie, S Zha, ... The Journal of Machine Learning Research 21 (1), 845-851, 2020 | 178 | 2020 |
| Star-gcn: Stacked and reconstructed graph convolutional networks for recommender systems J Zhang, X Shi, S Zhao, I King arXiv preprint arXiv:1905.13129, 2019 | 172 | 2019 |
| Relational stacked denoising autoencoder for tag recommendation H Wang, X Shi, DY Yeung Proceedings of the AAAI conference on artificial intelligence 29 (1), 2015 | 154 | 2015 |
| Collaborative recurrent autoencoder: Recommend while learning to fill in the blanks H Wang, X Shi, DY Yeung Advances in Neural Information Processing Systems 29, 2016 | 114 | 2016 |
| Machine learning for spatiotemporal sequence forecasting: A survey X Shi, DY Yeung arXiv preprint arXiv:1808.06865, 2018 | 99 | 2018 |
| Relational deep learning: A deep latent variable model for link prediction H Wang, X Shi, DY Yeung Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 73 | 2017 |
| Natural-parameter networks: A class of probabilistic neural networks H Wang, X Shi, DY Yeung Advances in neural information processing systems 29, 2016 | 69 | 2016 |
| Symbolic music generation with transformer-gans A Muhamed, L Li, X Shi, S Yaddanapudi, W Chi, D Jackson, R Suresh, ... Proceedings of the AAAI conference on artificial intelligence 35 (1), 408-417, 2021 | 35 | 2021 |
| Benchmarking multimodal automl for tabular data with text fields X Shi, J Mueller, N Erickson, M Li, AJ Smola arXiv preprint arXiv:2111.02705, 2021 | 29* | 2021 |
| Distributed stochastic ADMM for matrix factorization ZQ Yu, XJ Shi, L Yan, WJ Li Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 29 | 2014 |
| Visual speaker identification and authentication by joint spatiotemporal sparse coding and hierarchical pooling JY Lai, SL Wang, AWC Liew, XJ Shi Information Sciences 373, 219-232, 2016 | 18 | 2016 |
| Earthformer: Exploring space-time transformers for earth system forecasting Z Gao, X Shi, H Wang, Y Zhu, YB Wang, M Li, DY Yeung Advances in Neural Information Processing Systems 35, 25390-25403, 2022 | 12 | 2022 |
| Removing batch normalization boosts adversarial training H Wang, A Zhang, S Zheng, X Shi, M Li, Z Wang International Conference on Machine Learning, 23433-23445, 2022 | 11 | 2022 |
| Visual Prompt Tuning for Test-time Domain Adaptation Y Gao, X Shi, Y Zhu, H Wang, Z Tang, X Zhou, M Li, DN Metaxas arXiv preprint arXiv:2210.04831, 2022 | 9 | 2022 |
| Deep learning and the weather forecasting problem: Precipitation nowcasting Z Gao, X Shi, H Wang, DY Yeung, W Woo, WK Wong Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote …, 2021 | 8 | 2021 |
Dit-Yan YeungChair Professor, Department of CSE, HKUST, Hong Kong在 cse.ust.hk 的电子邮件经过验证
