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ORCIDTiantian He 0001
Person information
- affiliation: Agency for Science, Technology and Research (A*STAR), Singapore
- affiliation: Nanyang Technological University, School of Computer Science and Engineering, Singapore
- affiliation (PhD 2017): Hong Kong Polytechnic University, Hong Kong
Other persons with the same name
- Tiantian He — disambiguation page
- Tiantian He 0002
![[0009-0006-8199-6146]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0009-0006-8199-6146")
— University College London, UK - Tiantian He 0003 — Sichuan University, Chengdu, China
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2020 – today
- 2025
[j25]Yu Lei, Limin Shen, Zhu Sun, Tiantian He, Shanshan Feng, Guanfeng Liu:
COSTA: Contrastive Spatial and Temporal Debiasing framework for next POI recommendation. Neural Networks 185: 107212 (2025)- [j24]Lizhong Yao, Yu Zhang, Ling Wang, Rui Li, Tiantian He:
Natural Gas Pipeline Leak Detection Based on Dual Feature Drift in Acoustic Signals. IEEE Trans. Ind. Informatics 21(2): 1950-1959 (2025) - [j23]Fanghui Bi, Tiantian He, Yew-Soon Ong, Xin Luo:
Graph Linear Convolution Pooling for Learning in Incomplete High-Dimensional Data. IEEE Trans. Knowl. Data Eng. 37(4): 1838-1852 (2025) - [i12]Zhendong Guo, Yew-Soon Ong, Tiantian He, Haitao Liu:
Co-Learning Bayesian Optimization. CoRR abs/2501.13332 (2025) - [i11]Hongxu Wang, Zhu Sun, Yingpeng Du, Lu Zhang, Tiantian He, Yew-Soon Ong:
Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization. CoRR abs/2502.13180 (2025) - 2024
- [j22]Tiantian He, Yang Liu, Yew-Soon Ong, Xiaohu Wu, Xin Luo:
Polarized message-passing in graph neural networks. Artif. Intell. 331: 104129 (2024) - [j21]Leming Zhou, Kechen Liu, Yonghong Wang, Hanshu Qin, Tiantian He:
A prediction method of diabetes comorbidity based on non-negative latent features. Neurocomputing 609: 128447 (2024) - [j20]Haicang Zhou, Tiantian He, Yew-Soon Ong, Gao Cong, Quan Chen:
Differentiable Clustering for Graph Attention. IEEE Trans. Knowl. Data Eng. 36(8): 3751-3764 (2024) - [j19]Fanghui Bi, Tiantian He, Xin Luo:
A Fast Nonnegative Autoencoder-Based Approach to Latent Feature Analysis on High-Dimensional and Incomplete Data. IEEE Trans. Serv. Comput. 17(3): 733-746 (2024) - [c17]Shanli Tan, Hao Cheng, Xiaohu Wu, Han Yu, Tiantian He, Yew Soon Ong, Chongjun Wang, Xiaofeng Tao:
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants. AAAI 2024: 15231-15239 - [c16]Mengmeng Chen, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew Soon Ong, Qiqi Liu, Qicheng Lao, Han Yu:
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning. NeurIPS 2024 - [c15]Haicang Zhou, Weiming Huang, Yile Chen, Tiantian He, Gao Cong, Yew Soon Ong:
Road Network Representation Learning with the Third Law of Geography. NeurIPS 2024 - [c14]Fanghui Bi, Tiantian He:
SCG: A Novel Spatiotemporal Coupling Graph Convolutional Network-Incorporated Approach for Dynamic QoS Estimation. SMC 2024: 635-640 - [c13]Zhixuan Duan, Zuo Wang, Fanghui Bi, Tiantian He:
Discrete Multi-View Feature Propagation Preserving Graph Clustering. SMC 2024: 641-646 - [i10]Haicang Zhou, Weiming Huang, Yile Chen, Tiantian He, Gao Cong, Yew-Soon Ong:
Road Network Representation Learning with the Third Law of Geography. CoRR abs/2406.04038 (2024) - [i9]Ben Cao, Tiantian He, Xue Li, Bin Wang, Xiaohu Wu, Qiang Zhang, Yew-Soon Ong:
Learning Structurally Stabilized Representations for Multi-modal Lossless DNA Storage. CoRR abs/2408.00779 (2024) - [i8]Zhilong Li, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew-Soon Ong, Mengmeng Chen, Qiqi Liu, Qicheng Lao, Han Yu:
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning. CoRR abs/2410.07286 (2024) - [i7]Mengmeng Chen, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew-Soon Ong, Qiqi Liu, Qicheng Lao, Han Yu:
Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning. CoRR abs/2410.19321 (2024) - [i6]Zhangfan Yang, Junkai Ji, Shan He, Jianqiang Li, Tiantian He, Ruibin Bai, Zexuan Zhu, Yew Soon Ong:
Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screening. CoRR abs/2411.06740 (2024) - 2023
- [j18]Lizhong Yao, Tiantian He, Haijun Luo:
Piggybacking on past problem for faster optimization in aluminum electrolysis process design. Eng. Appl. Artif. Intell. 126: 106937 (2023) - [j17]Yu Xie, Yanfeng Liang, Maoguo Gong, A. Kai Qin, Yew-Soon Ong, Tiantian He:
Semisupervised Graph Neural Networks for Graph Classification. IEEE Trans. Cybern. 53(10): 6222-6235 (2023) - [j16]Fanghui Bi, Tiantian He, Yuetong Xie, Xin Luo:
Two-Stream Graph Convolutional Network-Incorporated Latent Feature Analysis. IEEE Trans. Serv. Comput. 16(4): 3027-3042 (2023) - [i5]Shanli Tan, Hao Cheng, Xiaohu Wu, Han Yu, Tiantian He, Yew-Soon Ong, Chongjun Wang, Xiaofeng Tao:
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants. CoRR abs/2312.11391 (2023) - 2022
- [j15]Lizhong Yao, Wei Ding, Tiantian He, Shouxin Liu, Ling Nie:
A multiobjective prediction model with incremental learning ability by developing a multi-source filter neural network for the electrolytic aluminium process. Appl. Intell. 52(15): 17387-17409 (2022) - [j14]Tiantian He, Lu Bai, Yew-Soon Ong:
Vicinal Vertex Allocation for Matrix Factorization in Networks. IEEE Trans. Cybern. 52(8): 8047-8060 (2022) - [j13]Zhendong Guo, Yew-Soon Ong, Tiantian He, Haitao Liu:
Co-Learning Bayesian Optimization. IEEE Trans. Cybern. 52(9): 9820-9833 (2022) - [c12]Fanghui Bi, Tiantian He, Xin Luo:
A Two-Stream Light Graph Convolution Network-based Latent Factor Model for Accurate Cloud Service QoS Estimation. ICDM 2022: 855-860 - [i4]Tiantian He, Haicang Zhou, Yew-Soon Ong, Gao Cong:
Not All Neighbors Are Worth Attending to: Graph Selective Attention Networks for Semi-supervised Learning. CoRR abs/2210.07715 (2022) - 2021
- [j12]Wei Ding, Lizhong Yao, Yanyan Li, Wei Long, Jun Yi, Tiantian He:
Dynamic evolutionary model based on a multi-sampling inherited HAPFNN for an aluminium electrolysis manufacturing system. Appl. Soft Comput. 99: 106925 (2021) - [j11]Lun Hu, Xiangyu Pan, Hong Yan, Pengwei Hu, Tiantian He:
Exploiting higher-order patterns for community detection in attributed graphs. Integr. Comput. Aided Eng. 28(2): 207-218 (2021) - [j10]Tiantian He, Yew-Soon Ong, Pengwei Hu:
Multi-source propagation aware network clustering☆. Neurocomputing 453: 119-130 (2021) - [c11]Tiantian He, Yew Soon Ong, Lu Bai:
Learning Conjoint Attentions for Graph Neural Nets. NeurIPS 2021: 2641-2653 - [c10]Lizhong Yao, Tiantian He:
Fuzzy Community Detection with Multi-View Correlated Topics. WI/IAT (Workshop/Special Session) 2021: 307-313 - [i3]Tiantian He, Lu Bai, Yew-Soon Ong:
Graph Joint Attention Networks. CoRR abs/2102.03147 (2021) - 2020
- [j9]Xiaobing Han, Tiantian He, Yew-Soon Ong, Yanfei Zhong:
Precise object detection using adversarially augmented local/global feature fusion. Eng. Appl. Artif. Intell. 94: 103710 (2020) - [j8]Lu Bai, Yew-Soon Ong, Tiantian He, Abhishek Gupta:
Multi-task gradient descent for multi-task learning. Memetic Comput. 12(4): 355-369 (2020) - [j7]Tiantian He, Yang Liu, Tobey H. Ko, Keith C. C. Chan, Yew-Soon Ong:
Contextual Correlation Preserving Multiview Featured Graph Clustering. IEEE Trans. Cybern. 50(10): 4318-4331 (2020) - [i2]Tiantian He, Lu Bai, Yew-Soon Ong:
Relational Thematic Clustering with Mutually Preferred Neighbors. CoRR abs/2001.08412 (2020)
2010 – 2019
- 2019
- [j6]Tiantian He, Keith C. C. Chan:
Measuring Boundedness for Protein Complex Identification in PPI Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 16(3): 967-979 (2019) - [c9]Tiantian He, Lu Bai, Yew-Soon Ong:
Manifold Regularized Stochastic Block Model. ICTAI 2019: 800-807 - [i1]Lu Bai, Yew-Soon Ong, Tiantian He, Abhishek Gupta:
A Multi-Task Gradient Descent Method for Multi-Label Learning. CoRR abs/1911.07693 (2019) - 2018
- [j5]Tiantian He, Lun Hu, Keith C. C. Chan, Pengwei Hu:
Learning Latent Factors for Community Identification and Summarization. IEEE Access 6: 30137-30148 (2018) - [j4]Yan-Xing Hu, Jane Jia You, James N. K. Liu, Tiantian He:
An eigenvector based center selection for fast training scheme of RBFNN. Inf. Sci. 428: 62-75 (2018) - [j3]Tiantian He, Keith C. C. Chan:
Evolutionary Graph Clustering for Protein Complex Identification. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 892-904 (2018) - [j2]Tiantian He, Keith C. C. Chan:
MISAGA: An Algorithm for Mining Interesting Subgraphs in Attributed Graphs. IEEE Trans. Cybern. 48(5): 1369-1382 (2018) - [j1]Tiantian He, Keith C. C. Chan:
Discovering Fuzzy Structural Patterns for Graph Analytics. IEEE Trans. Fuzzy Syst. 26(5): 2785-2796 (2018) - [c8]Pengwei Hu, Zhaomeng Niu, Tiantian He, Keith C. C. Chan:
Learning Deep Representations in Large Integrated Network for Graph Clustering. AIKE 2018: 101-105 - [c7]Pengwei Hu, Zhu-Hong You, Tiantian He, Shaochun Li, Shuhang Gu, Keith C. C. Chan:
Learning Latent Patterns in Molecular Data for Explainable Drug Side Effects Prediction. BIBM 2018: 1163-1169 - [c6]Tiantian He, Keith C. C. Chan:
Learning Latent Factors in Linked Multi-modality Data. ISMIS 2018: 214-224 - [c5]Tobey H. Ko, Zhonglei Gu, Tiantian He, Yang Liu:
Towards Learning Emotional Subspace. MediaEval 2018 - [c4]Tiantian He, Keith C. C. Chan, Libin Yang:
Clustering in Networks with Multi-Modality Attributes. WI 2018: 401-406 - 2017
- [c3]Pengwei Hu, Tiantian He, Keith C. C. Chan, Henry Leung:
Deep Fusion of Multiple Networks for Learning Latent Social Communities. ICTAI 2017: 765-771 - [c2]Pengwei Hu, Keith C. C. Chan, Tiantian He:
Deep Graph Clustering in Social Network. WWW (Companion Volume) 2017: 1425-1426 - 2014
- [c1]Tiantian He, Keith C. C. Chan:
Evolutionary community detection in social networks. IEEE Congress on Evolutionary Computation 2014: 1496-1503
Coauthor Index
aka: Yew Soon Ong
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