| 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 | 7178 | 2015 |
| Collaborative deep learning for recommender systems H Wang, N Wang, DY Yeung Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 1725 | 2015 |
| Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model X Shi, H Wang, Z Gao, L Lausen, DY Yeung, W WOO, W Wong Advances in Neural Information Processing Systems, 5620-5630, 2017 | 621 | 2017 |
| Rethinking knowledge graph propagation for zero-shot learning M Kampffmeyer, Y Chen, X Liang, H Wang, Y Zhang, EP Xing Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 296 | 2019 |
| Towards Bayesian Deep Learning: A Framework and Some Existing Methods H Wang, DY Yeung IEEE Transactions on Knowledge and Data Engineering 28 (12), 3395-3408, 2016, 2016 | 280 | 2016 |
| Collaborative Topic Regression with Social Regularization for Tag Recommendation. H Wang, B Chen, WJ Li International Joint Conference on Artificial Intelligence (IJCAI), 2719-2725, 2013 | 167 | 2013 |
| Relational Stacked Denoising Autoencoder for Tag Recommendation. H Wang, X Shi, DY Yeung AAAI Conference on Artificial Intelligence (AAAI), 3052-3058, 2015 | 154 | 2015 |
| Extracting Multi-Person Respiration from Entangled RF Signals S Yue, H He, H Wang, H Rahul, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 126 | 2018 |
| A Survey on Bayesian Deep Learning H Wang, DY Yeung ACM Computing Surveys (CSUR) 53 (5), 1-37, 2020 | 116 | 2020 |
| 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 | 113 | 2016 |
| Delving into Deep Imbalanced Regression Y Yang, K Zha, YC Chen, H Wang, D Katabi International Conference on Machine Learning (ICML), 2021 | 108 | 2021 |
| Continuously Indexed Domain Adaptation H Wang, H He, D Katabi International Conference on Machine Learning (ICML), 2020 | 76 | 2020 |
| Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. H Wang, X Shi, DY Yeung AAAI Conference on Artificial Intelligence (AAAI), 2688-2694, 2017 | 73 | 2017 |
| Deep Learning and the Weather Forecasting Problem: Precipitation Nowcasting Z Gao, X Shi, H Wang, DY Yeung, W Woo, WK Wong Book Chapter of Deep Learning for the Earth Sciences: A Comprehensive …, 2021 | 69* | 2021 |
| Natural-parameter networks: A class of probabilistic neural networks H Wang, X Shi, DY Yeung Advances in neural information processing systems 29, 2016 | 67 | 2016 |
| Relational collaborative topic regression for recommender systems H Wang, WJ Li IEEE Transactions on Knowledge and Data Engineering 27 (5), 1343-1355, 2015 | 65 | 2015 |
| BodyCompass: Monitoring Sleep Posture with Wireless Signals S Yue, Y Yang, H Wang, H Rahul, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2020 | 58 | 2020 |
| ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees H He, H Wang, GH Lee, Y Tian International Conference on Learning Representations (ICLR), 2019 | 38* | 2019 |
| Paint transformer: Feed forward neural painting with stroke prediction S Liu, T Lin, D He, F Li, R Deng, X Li, E Ding, H Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 36 | 2021 |
| ZM-Net: Real-time Zero-shot Image Manipulation Network H Wang, X Liang, H Zhang, DY Yeung, EP Xing arXiv preprint arXiv:1703.07255, 2017 | 36 | 2017 |
Dit-Yan YeungChair Professor, Department of CSE, HKUST, Hong KongVerified email at cse.ust.hk
