Exploring Spatio-Temporal Representations by Integrating Attention-based Bidirectional-LSTM-RNNs and FCNs for Speech Emotion Recognition. - Ziping Zhao 001; Yu Zheng 013; Zixing Zhang 001; Haishuai Wang; Yiqin Zhao; Chao Li (INTERSPEECH, 2018)

A LSTM Based Model for Personalized Context-Aware Citation Recommendation. - Libin Yang; Yu Zheng 013; Xiaoyan Cai; Hang Dai; Dejun Mu; Lantian Guo; Tao Dai 002 (IEEE Access, 2018)

Query-oriented citation recommendation based on network correlation. - Libin Yang; Yu Zheng 013; Xiaoyan Cai; Shirui Pan; Tao Dai 002 (J. Intell. Fuzzy Syst., 2018)

Feature-Dependent Graph Convolutional Autoencoders with Adversarial Training Methods. - Di Wu 050; Ruiqi Hu; Yu Zheng 013; Jing Jiang 002; Nabin Sharma; Michael Blumenstein (IJCNN, 2019)

Bibliographic Network Representation Based Personalized Citation Recommendation. - Xiaoyan Cai; Yu Zheng 013; Libin Yang; Tao Dai 002; Lantian Guo (IEEE Access, 2019)

Joint Model Feature Regression and Topic Learning for Global Citation Recommendation. - Tao Dai 002; Li Zhu 003; Yifan Wang; Hongfei Zhang; Xiaoyan Cai; Yu Zheng 013 (IEEE Access, 2019)

Searching Correlated Patterns From Graph Streams. - Ming Jin 005; Mei Li; Yu Zheng 013; Lianhua Chi (IEEE Access, 2020)

A Tri-Attention Neural Network Model-BasedRecommendation. - Nanxin Wang; Libin Yang; Yu Zheng 013; Xiaoyan Cai; Xin Mei; Hang Dai (Complex., 2020)

Clustering social audiences in business information networks. - Yu Zheng 013; Ruiqi Hu; Sai-Fu Fung; Celina Ping Yu; Guodong Long; Ting Guo; Shirui Pan (Pattern Recognit., 2020)

ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning. - Ming Jin 005; Yixin Liu 001; Yu Zheng 013; Lianhua Chi; Yuan-Fang Li; Shirui Pan (CIKM, 2021)

Selection strategy in graph-based spreading dynamics with limited capacity. - Fei Xiong; Yu Zheng 013; Weiping Ding 001; Hao Wang 003; Xinyi Wang; Hongshu Chen (Future Gener. Comput. Syst., 2021)

Unifying Graph Contrastive Learning with Flexible Contextual Scopes. - Yizhen Zheng; Yu Zheng 013; Xiaofei Zhou; Chen Gong 002; Vincent C. S. Lee; Shirui Pan (ICDM, 2022)

Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. - Yizhen Zheng; Shirui Pan; Vincent C. S. Lee; Yu Zheng 013; Philip S. Yu (NeurIPS, 2022)

Towards Unsupervised Deep Graph Structure Learning. - Yixin Liu 001; Yu Zheng 013; Daokun Zhang; Hongxu Chen 002; Hao Peng 001; Shirui Pan (WWW, 2022)

From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach. - Yu Zheng 013; Ming Jin 005; Yixin Liu 001; Lianhua Chi; Khoa Tran Phan; Shirui Pan; Yi-Ping Phoebe Chen (CoRR, 2022)

Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs. - Yizhen Zheng; He Zhang 012; Vincent Cheng-Siong Lee; Yu Zheng 013; Xiao Wang; Shirui Pan (ICML, 2023)

Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook. - Ming Jin 005; Qingsong Wen; Yuxuan Liang; Chaoli Zhang 001; Siqiao Xue; Xue Wang 010; James Zhang; Yi Wang 022; Haifeng Chen; Xiaoli Li 001; Shirui Pan; Vincent S. Tseng; et al. (CoRR, 2023)

Graph Self-Supervised Learning: A Survey. - Yixin Liu 001; Ming Jin 005; Shirui Pan; Chuan Zhou 001; Yu Zheng 013; Feng Xia 001; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2023)

Multivariate Time Series Forecasting With Dynamic Graph Neural ODEs. - Ming Jin 005; Yu Zheng 013; Yuan-Fang Li; Siheng Chen; Bin Yang 002; Shirui Pan (IEEE Trans. Knowl. Data Eng., 2023)

Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection. - Yu Zheng 013; Ming Jin 005; Yixin Liu 001; Lianhua Chi; Khoa Tran Phan; Yi-Ping Phoebe Chen (IEEE Trans. Knowl. Data Eng., 2023)

ARC: A Generalist Graph Anomaly Detector with In-Context Learning. - Yixin Liu 001; Shiyuan Li; Yu Zheng 013; Qingfeng Chen; Chengqi Zhang; Shirui Pan (NeurIPS, 2024)

Graph Contrastive Learning with Kernel Dependence Maximization for Social Recommendation. - Xuelian Ni; Fei Xiong; Yu Zheng 013; Liang Wang 017 (WWW, 2024)

Graph spatiotemporal process for multivariate time series anomaly detection with missing values. - Yu Zheng 013; Huan Yee Koh; Ming Jin 005; Lianhua Chi; Haishuai Wang; Khoa Tran Phan; Yi-Ping Phoebe Chen; Shirui Pan; Wei Xiang 001 (Inf. Fusion, 2024)

LGCDA: Predicting CircRNA-Disease Association Based on Fusion of Local and Global Features. - Wei Lan; Chunling Li; Qingfeng Chen; Ning Yu 004; Yi Pan 001; Yu Zheng 013; Yi-Ping Phoebe Chen (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

Correlation-Aware Spatial-Temporal Graph Learning for Multivariate Time-Series Anomaly Detection. - Yu Zheng 013; Huan Yee Koh; Ming Jin 005; Lianhua Chi; Khoa Tran Phan; Shirui Pan; Yi-Ping Phoebe Chen; Wei Xiang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)