| Convolutional LSTM network: A machine learning approach for precipitation nowcasting X Shi, Z Chen, H Wang, DY Yeung, WK Wong, W Woo arXiv preprint arXiv:1506.04214, 2015 | 2905 | 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 arXiv preprint arXiv:1706.03458, 2017 | 169 | 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 | 157 | 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 | 112 | 2017 |
| Relational stacked denoising autoencoder for tag recommendation H Wang, X Shi, DY Yeung Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 112 | 2015 |
| 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 | 99 | 2017 |
| Collaborative recurrent autoencoder: Recommend while learning to fill in the blanks H Wang, X Shi, DY Yeung arXiv preprint arXiv:1611.00454, 2016 | 79 | 2016 |
| 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, ... Journal of Machine Learning Research 21 (23), 1-7, 2020 | 48 | 2020 |
| 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 | 41 | 2017 |
| Machine learning for spatiotemporal sequence forecasting: A survey X Shi, DY Yeung arXiv preprint arXiv:1808.06865, 2018 | 32 | 2018 |
| 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 | 30 | 2019 |
| Natural-parameter networks: A class of probabilistic neural networks H Wang, X Shi, DY Yeung arXiv preprint arXiv:1611.00448, 2016 | 24 | 2016 |
| 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 | 23 | 2014 |
| Quantum language processing N Wiebe, A Bocharov, P Smolensky, M Troyer, KM Svore arXiv preprint arXiv:1902.05162, 2019 | 13 | 2019 |
| 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 | 11 | 2016 |
| A deep-learning method for precipitation nowcasting W Wong, XJ Shi, DY Yeung, WC Woo WMO WWRP 4th International Symposium on Nowcasting and Veryshort-range …, 2016 | 4 | 2016 |
| Sparse coding based lip texture representation for visual speaker identification JY Lai, SL Wang, XJ Shi, AWC Liew 2014 19th International Conference on Digital Signal Processing, 607-610, 2014 | 3 | 2014 |
| Denoising predictive sparse decomposition L Qian, X Shi 2014 International Conference on Big Data and Smart Computing (BIGCOMP), 223-228, 2014 | 1 | 2014 |
| Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data J Mueller, X Shi, A Smola Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | | 2020 |
| Dive into Deep Learning for Natural Language Processing H Lin, X Shi, L Lausen, A Zhang, H He, S Zha, A Smola Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | | 2019 |
Dit-Yan YeungChair Professor and Head of CSE Department, HKUST, Hong KongVerified email at cse.ust.hk
