| 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 | 10808 | 2015 |
| Dataset Meta-Learning from Kernel Ridge-Regression T Nguyen, Z Chen, J Lee International Conference on Learning Representations (ICLR), 2021 | 263 | 2021 |
| Screen2words: Automatic mobile UI summarization with multimodal learning B Wang, G Li, X Zhou, Z Chen, T Grossman, Y Li The 34th Annual ACM Symposium on User Interface Software and Technology, 498-510, 2021 | 142 | 2021 |
| You look twice: Gaternet for dynamic filter selection in cnns Z Chen, Y Li, S Bengio, S Si Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern
, 2019 | 130* | 2019 |
| Convolutional LSTM network: A machine learning approach for precipitation nowcasting. arXiv 2015 X Shi, Z Chen, H Wang, DY Yeung, WK Wong, WC Woo arXiv preprint arXiv:1506.04214, 2015 | 100 | 2015 |
| Learning Latent Superstructures in Variational Autoencoders for Deep Multidimensional Clustering X Li, Z Chen, LKM Poon, NL Zhang International Conference on Learning Representations, 2019 | 77 | 2019 |
| Latent tree models for hierarchical topic detection P Chen, NL Zhang, T Liu, LKM Poon, Z Chen, F Khawar Artificial Intelligence 250, 105-124, 2017 | 69 | 2017 |
| WOO, W.-c.(2015) X Shi, Z Chen, H Wang, DY Yeung, WK Wong Convolutional lstm network: A machine learning approach for precipitation
, 0 | 48 | |
| Progressive EM for latent tree models and hierarchical topic detection P Chen, NL Zhang, LKM Poon, Z Chen Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 35 | 2016 |
| Predicting and explaining mobile ui tappability with vision modeling and saliency analysis E Schoop, X Zhou, G Li, Z Chen, B Hartmann, Y Li Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
, 2022 | 30 | 2022 |
| Identification and classification of traditional Chinese medicine syndrome types among senior patients with vascular mild cognitive impairment using latent tree analysis C Fu, NL Zhang, B Chen, ZR Chen, XL Jin, R Guo, Z Chen, Y Zhang Journal of integrative medicine 15 (3), 186-200, 2017 | 21 | 2017 |
| Sparse Boltzmann machines with structure learning as applied to text analysis Z Chen, N Zhang, DY Yeung, P Chen Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 16 | 2017 |
| Convolutional LSTM network: A machine learning approach for precipitation nowcasting, CoRR abs/1506.04214 (2015) X Shi, Z Chen, H Wang, D Yeung, W Wong, W Woo arXiv preprint arXiv:1506.04214, 2015 | 14 | 2015 |
| Wang-chun WOO. 2015. Convolutional LSTM network: A machine learning approach for precipitation nowcasting X Shi, Z Chen Advances in Neural Information Processing Systems, C. Cortes, N. Lawrence, D
, 0 | 14 | |
| Wai-kinWong, and Wang-chun Woo. 2015. X Shi, Z Chen Convolutional LSTM network: A machine learning approach for precipitation
, 2015 | 7 | 2015 |
| Convolutional LSTM network: A machine learning approach for precipitation nowcasting, CoRR abs/1506.04214 X Shi, Z Chen, H Wang, D Yeung, W Wong, W Woo arXiv preprint arXiv:1506.04214, 2015 | 7 | 2015 |
| Wang-chun WOO. 2015 X Shi, Z Chen Convolutional LSTM Network: A Machine Learning Approach for Precipitation
, 0 | 6 | |
| Convolutional lstm network: A machine learning approach for precipitation nowcasting. arXiv preprint, 2015 X Shi, Z Chen, H Wang, DY Yeung, WK Wong, W Woo URL https://arxiv. org/abs/1506.04214, 0 | 6 | |
| kin Wong W., chun Woo W X Shi, Z Chen, H Wang, DY Yeung Convolutional LSTM Network: A Machine Learning Approach for Precipitation
, 2015 | 5 | 2015 |
| Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World B Ni, X Wang, Q Zhang, P Tang, Z Chen, T Yin, L Lu, X Liu, K Sun, Z Ma Proceedings of the ACM Web Conference 2023, 3417-3427, 2023 | 3 | 2023 |
Xingjian ShiBoson AIPatvirtintas el. paštas connect.ust.hk
