Yuxuan Liang
Title
Cited by
Cited by
Year
GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction.
Y Liang, S Ke, J Zhang, X Yi, Y Zheng
IJCAI 2018, 3428-3434, 2018
1962018
Urban water quality prediction based on multi-task multi-view learning
Y Liu, Y Zheng, Y Liang, S Liu, DS Rosenblum
IJCAI 2016, 2016
1912016
Urban traffic prediction from spatio-temporal data using deep meta learning
Z Pan, Y Liang, W Wang, Y Yu, Y Zheng, J Zhang
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
1072019
Predicting urban water quality with ubiquitous data
Y Liu, Y Liang, S Liu, DS Rosenblum, Y Zheng
arXiv preprint arXiv:1610.09462, 2016
46*2016
Urbanfm: Inferring fine-grained urban flows
Y Liang, K Ouyang, L Jing, S Ruan, Y Liu, J Zhang, DS Rosenblum, ...
proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019
442019
Predicting citywide crowd flows in irregular regions using multi-view graph convolutional networks
J Sun, J Zhang, Q Li, X Yi, Y Liang, Y Zheng
IEEE Transactions on Knowledge and Data Engineering, 2020
382020
Federated forest
Y Liu, Y Liu, Z Liu, Y Liang, C Meng, J Zhang, Y Zheng
IEEE Transactions on Big Data, 2020
342020
Inferring traffic cascading patterns
Y Liang, Z Jiang, Y Zheng
Proceedings of the 25th acm sigspatial international conference on advances …, 2017
272017
Nodeaug: Semi-supervised node classification with data augmentation
Y Wang, W Wang, Y Liang, Y Cai, J Liu, B Hooi
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
162020
Fine-grained urban flow inference
K Ouyang, Y Liang, Y Liu, Z Tong, S Ruan, D Rosenblum, Y Zheng
IEEE Transactions on Knowledge and Data Engineering, 2020
132020
Autost: Efficient neural architecture search for spatio-temporal prediction
T Li, J Zhang, K Bao, Y Liang, Y Li, Y Zheng
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
122020
Urban water quality prediction based on multi-task multi-view learning (IJCAI)
Y Liu, Y Zheng, Y Liang, S Liu, DS Rosenblum
Google Scholar Google Scholar Digital Library Digital Library, 2016
12*2016
Learning to generate maps from trajectories
S Ruan, C Long, J Bao, C Li, Z Yu, R Li, Y Liang, T He, Y Zheng
Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 890-897, 2020
112020
Spatio-temporal meta learning for urban traffic prediction
Z Pan, W Zhang, Y Liang, W Zhang, Y Yu, J Zhang, Y Zheng
IEEE Transactions on Knowledge and Data Engineering, 2020
102020
Directed graph convolutional network
Z Tong, Y Liang, C Sun, DS Rosenblum, A Lim
arXiv preprint arXiv:2004.13970, 2020
102020
Hyperst-net: Hypernetworks for spatio-temporal forecasting
Z Pan, Y Liang, J Zhang, X Yi, Y Yu, Y Zheng
arXiv preprint arXiv:1809.10889, 2018
102018
Graphcrop: Subgraph cropping for graph classification
Y Wang, W Wang, Y Liang, Y Cai, B Hooi
arXiv preprint arXiv:2009.10564, 2020
62020
Revisiting convolutional neural networks for citywide crowd flow analytics
Y Liang, K Ouyang, Y Wang, Y Liu, J Zhang, Y Zheng, DS Rosenblum
arXiv preprint arXiv:2003.00895, 2020
5*2020
Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking.
N Wanigasekara, Y Liang, ST Goh, Y Liu, JJ Williams, DS Rosenblum
IJCAI, 3835-3841, 2019
52019
Digraph inception convolutional networks
Z Tong, Y Liang, C Sun, X Li, D Rosenblum, A Lim
Advances in neural information processing systems 33, 2020
42020
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