Evolutionary community detection in social networks. - Tiantian He 001; Keith C. C. Chan (IEEE Congress on Evolutionary Computation, 2014)

Deep Fusion of Multiple Networks for Learning Latent Social Communities. - Pengwei Hu 001; Tiantian He 001; Keith C. C. Chan; Henry Leung (ICTAI, 2017)

Deep Graph Clustering in Social Network. - Pengwei Hu 001; Keith C. C. Chan; Tiantian He 001 (WWW (Companion Volume), 2017)

Learning Deep Representations in Large Integrated Network for Graph Clustering. - Pengwei Hu 001; Zhaomeng Niu; Tiantian He 001; Keith C. C. Chan (AIKE, 2018)

Learning Latent Patterns in Molecular Data for Explainable Drug Side Effects Prediction. - Pengwei Hu 001; Zhu-Hong You; Tiantian He 001; Shaochun Li; Shuhang Gu; Keith C. C. Chan (BIBM, 2018)

Learning Latent Factors in Linked Multi-modality Data. - Tiantian He 001; Keith C. C. Chan (ISMIS, 2018)

Towards Learning Emotional Subspace. - Tobey H. Ko; Zhonglei Gu; Tiantian He 001; Yang Liu 007 (MediaEval, 2018)

Clustering in Networks with Multi-Modality Attributes. - Tiantian He 001; Keith C. C. Chan; Libin Yang (WI, 2018)

Learning Latent Factors for Community Identification and Summarization. - Tiantian He 001; Lun Hu; Keith C. C. Chan; Pengwei Hu 001 (IEEE Access, 2018)

An eigenvector based center selection for fast training scheme of RBFNN. - Yan-Xing Hu; Jane Jia You; James N. K. Liu; Tiantian He 001 (Inf. Sci., 2018)

Evolutionary Graph Clustering for Protein Complex Identification. - Tiantian He 001; Keith C. C. Chan (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

MISAGA: An Algorithm for Mining Interesting Subgraphs in Attributed Graphs. - Tiantian He 001; Keith C. C. Chan (IEEE Trans. Cybern., 2018)

Discovering Fuzzy Structural Patterns for Graph Analytics. - Tiantian He 001; Keith C. C. Chan (IEEE Trans. Fuzzy Syst., 2018)

Manifold Regularized Stochastic Block Model. - Tiantian He 001; Lu Bai 005; Yew-Soon Ong (ICTAI, 2019)

A Multi-Task Gradient Descent Method for Multi-Label Learning. - Lu Bai 005; Yew-Soon Ong; Tiantian He 001; Abhishek Gupta 001 (CoRR, 2019)

Measuring Boundedness for Protein Complex Identification in PPI Networks. - Tiantian He 001; Keith C. C. Chan (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Relational Thematic Clustering with Mutually Preferred Neighbors. - Tiantian He 001; Lu Bai 005; Yew-Soon Ong (CoRR, 2020)

Precise object detection using adversarially augmented local/global feature fusion. - Xiaobing Han; Tiantian He 001; Yew-Soon Ong; Yanfei Zhong (Eng. Appl. Artif. Intell., 2020)

Multi-task gradient descent for multi-task learning. - Lu Bai 005; Yew-Soon Ong; Tiantian He 001; Abhishek Gupta 001 (Memetic Comput., 2020)

Contextual Correlation Preserving Multiview Featured Graph Clustering. - Tiantian He 001; Yang Liu 007; Tobey H. Ko; Keith C. C. Chan; Yew-Soon Ong (IEEE Trans. Cybern., 2020)

Learning Conjoint Attentions for Graph Neural Nets. - Tiantian He 001; Yew Soon Ong; Lu Bai 005 (NeurIPS, 2021)

Fuzzy Community Detection with Multi-View Correlated Topics. - Lizhong Yao; Tiantian He 001 (WI/IAT (Workshop/Special Session), 2021)

Dynamic evolutionary model based on a multi-sampling inherited HAPFNN for an aluminium electrolysis manufacturing system. - Wei Ding; Lizhong Yao; Yanyan Li; Wei Long; Jun Yi; Tiantian He 001 (Appl. Soft Comput., 2021)

Graph Joint Attention Networks. - Tiantian He 001; Lu Bai 005; Yew-Soon Ong (CoRR, 2021)

Exploiting higher-order patterns for community detection in attributed graphs. - Lun Hu; Xiangyu Pan; Hong Yan 001; Pengwei Hu 001; Tiantian He 001 (Integr. Comput. Aided Eng., 2021)

Multi-source propagation aware network clustering☆. - Tiantian He 001; Yew-Soon Ong; Pengwei Hu 001 (Neurocomputing, 2021)

A Two-Stream Light Graph Convolution Network-based Latent Factor Model for Accurate Cloud Service QoS Estimation. - Fanghui Bi; Tiantian He 001; Xin Luo 001 (ICDM, 2022)

A multiobjective prediction model with incremental learning ability by developing a multi-source filter neural network for the electrolytic aluminium process. - Lizhong Yao; Wei Ding; Tiantian He 001; Shouxin Liu; Ling Nie (Appl. Intell., 2022)

Not All Neighbors Are Worth Attending to: Graph Selective Attention Networks for Semi-supervised Learning. - Tiantian He 001; Haicang Zhou; Yew-Soon Ong; Gao Cong (CoRR, 2022)

Co-Learning Bayesian Optimization. - Zhendong Guo; Yew-Soon Ong; Tiantian He 001; Haitao Liu 002 (IEEE Trans. Cybern., 2022)

Vicinal Vertex Allocation for Matrix Factorization in Networks. - Tiantian He 001; Lu Bai 005; Yew-Soon Ong (IEEE Trans. Cybern., 2022)

Two-Stream Graph Convolutional Network-Incorporated Latent Feature Analysis. - Fanghui Bi; Tiantian He 001; Yuetong Xie; Xin Luo 001 (IEEE Trans. Serv. Comput., 2023)

Semisupervised Graph Neural Networks for Graph Classification. - Yu Xie; Yanfeng Liang; Maoguo Gong; A. Kai Qin; Yew-Soon Ong; Tiantian He 001 (IEEE Trans. Cybern., 2023)

Piggybacking on past problem for faster optimization in aluminum electrolysis process design. - Lizhong Yao; Tiantian He 001; Haijun Luo (Eng. Appl. Artif. Intell., 2023)

FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants. - Shanli Tan; Hao Cheng 014; Xiaohu Wu; Han Yu 001; Tiantian He 001; Yew Soon Ong; Chongjun Wang; Xiaofeng Tao (AAAI, 2024)

Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning. - Mengmeng Chen; Xiaohu Wu; Xiaoli Tang 001; Tiantian He 001; Yew Soon Ong; Qiqi Liu; Qicheng Lao; Han Yu 001 (NeurIPS, 2024)

Road Network Representation Learning with the Third Law of Geography. - Haicang Zhou; Weiming Huang 001; Yile Chen 001; Tiantian He 001; Gao Cong; Yew Soon Ong (NeurIPS, 2024)

SCG: A Novel Spatiotemporal Coupling Graph Convolutional Network-Incorporated Approach for Dynamic QoS Estimation. - Fanghui Bi; Tiantian He 001 (SMC, 2024)

Discrete Multi-View Feature Propagation Preserving Graph Clustering. - Zhixuan Duan; Zuo Wang; Fanghui Bi; Tiantian He 001 (SMC, 2024)

Polarized message-passing in graph neural networks. - Tiantian He 001; Yang Liu 007; Yew-Soon Ong; Xiaohu Wu; Xin Luo 001 (Artif. Intell., 2024)

Learning Structurally Stabilized Representations for Multi-modal Lossless DNA Storage. - Ben Cao; Tiantian He 001; Xue Li; Bin Wang 005; Xiaohu Wu; Qiang Zhang 008; Yew-Soon Ong (CoRR, 2024)

Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning. - Zhilong Li; Xiaohu Wu; Xiaoli Tang 001; Tiantian He 001; Yew-Soon Ong; Mengmeng Chen; Qiqi Liu; Qicheng Lao; Han Yu 001 (CoRR, 2024)

Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screening. - Zhangfan Yang; Junkai Ji; Shan He 001; Jianqiang Li 001; Tiantian He 001; Ruibin Bai; Zexuan Zhu; Yew Soon Ong (CoRR, 2024)

A prediction method of diabetes comorbidity based on non-negative latent features. - Leming Zhou; Kechen Liu; Yonghong Wang; Hanshu Qin; Tiantian He 001 (Neurocomputing, 2024)

Differentiable Clustering for Graph Attention. - Haicang Zhou; Tiantian He 001; Yew-Soon Ong; Gao Cong; Quan Chen (IEEE Trans. Knowl. Data Eng., 2024)

A Fast Nonnegative Autoencoder-Based Approach to Latent Feature Analysis on High-Dimensional and Incomplete Data. - Fanghui Bi; Tiantian He 001; Xin Luo 001 (IEEE Trans. Serv. Comput., 2024)

COSTA: Contrastive Spatial and Temporal Debiasing framework for next POI recommendation. - Yu Lei; Limin Shen; Zhu Sun 001; Tiantian He 001; Shanshan Feng 001; Guanfeng Liu 001 (Neural Networks, 2025)

Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization. - Hongxu Wang; Zhu Sun 001; Yingpeng Du; Lu Zhang 063; Tiantian He 001; Yew-Soon Ong (CoRR, 2025)

Natural Gas Pipeline Leak Detection Based on Dual Feature Drift in Acoustic Signals. - Lizhong Yao; Yu Zhang; Ling Wang 001; Rui Li 087; Tiantian He 001 (IEEE Trans. Ind. Informatics, 2025)

Graph Linear Convolution Pooling for Learning in Incomplete High-Dimensional Data. - Fanghui Bi; Tiantian He 001; Yew-Soon Ong; Xin Luo 001 (IEEE Trans. Knowl. Data Eng., 2025)

BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs. - Junxiao Yang; Jinzhe Tu; Haoran Liu; Xiaoce Wang; Chujie Zheng; Zhexin Zhang; Shiyao Cui; Caishun Chen; Tiantian He 001; Hongning Wang; Yew-Soon Ong; Minlie Huang (CoRR, 2025)

Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning. - Mengmeng Chen; Xiaohu Wu; Qiqi Liu; Tiantian He 001; Yew-Soon Ong; Yaochu Jin; Qicheng Lao; Han Yu 001 (CoRR, 2025)

Context-Adaptive Graph Neural Networks for Next POI Recommendation. - Yu Lei; Limin Shen; Zhu Sun 001; Tiantian He 001; Yew-Soon Ong (CoRR, 2025)