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2020 – today
- 2024
[j22]Wei Ju
, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang:
COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting. Inf. Fusion 107: 102341 (2024)- [j21]Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang:
A Comprehensive Survey on Deep Graph Representation Learning. Neural Networks 173: 106207 (2024) - [j20]Wei Ju, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Siyu Yi, Zhiping Xiao, Xiao Luo, Yanjie Fu, Ming Zhang:
Focus on informative graphs! Semi-supervised active learning for graph-level classification. Pattern Recognit. 153: 110567 (2024) - [j19]Xiao Luo, Wei Ju, Yiyang Gu, Zhengyang Mao, Luchen Liu, Yuhui Yuan, Ming Zhang:
Self-supervised Graph-level Representation Learning with Adversarial Contrastive Learning. ACM Trans. Knowl. Discov. Data 18(2): 34:1-34:23 (2024) - [j18]Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang:
Towards Semi-Supervised Universal Graph Classification. IEEE Trans. Knowl. Data Eng. 36(1): 416-428 (2024) - [j17]Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang:
Learning Graph ODE for Continuous-Time Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 36(7): 3224-3236 (2024) - [j16]Xiao Luo, Wei Ju, Meng Qu, Yiyang Gu, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
CLEAR: Cluster-Enhanced Contrast for Self-Supervised Graph Representation Learning. IEEE Trans. Neural Networks Learn. Syst. 35(1): 899-912 (2024) - [j15]Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang:
A Diffusion Model for POI Recommendation. ACM Trans. Inf. Syst. 42(2): 54:1-54:27 (2024) - [j14]Xiao Luo, Wei Ju, Yiyang Gu, Yifang Qin, Siyu Yi, Daqing Wu, Luchen Liu, Ming Zhang:
Toward Effective Semi-supervised Node Classification with Hybrid Curriculum Pseudo-labeling. ACM Trans. Multim. Comput. Commun. Appl. 20(3): 82:1-82:19 (2024) - [c24]Wei Ju, Siyu Yi, Ming Zhang:
Evidential Self-Supervised Graph Representation Learning via Prototype-based Consistency. ACM TUR-C 2024 - [c23]Qingqing Long, Yuchen Yan, Wentao Cui, Wei Ju, Zhihong Zhu, Yuanchun Zhou, Xuezhi Wang, Meng Xiao:
MOAT: Graph Prompting for 3D Molecular Graphs. CIKM 2024: 1586-1596 - [c22]Xiao Luo, Yiyang Gu, Huiyu Jiang, Hang Zhou, Jinsheng Huang, Wei Ju, Zhiping Xiao, Ming Zhang, Yizhou Sun:
PGODE: Towards High-quality System Dynamics Modeling. ICML 2024 - [c21]Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang:
Hypergraph-enhanced Dual Semi-supervised Graph Classification. ICML 2024 - [c20]Junyu Luo, Zhiping Xiao, Yifan Wang, Xiao Luo, Jingyang Yuan, Wei Ju, Langechuan Liu, Ming Zhang:
Rank and Align: Towards Effective Source-free Graph Domain Adaptation. IJCAI 2024: 4706-4714 - [c19]Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, Ming Zhang:
A Survey of Data-Efficient Graph Learning. IJCAI 2024: 8104-8113 - [i30]Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, Ming Zhang:
A Survey on Graph Neural Networks in Intelligent Transportation Systems. CoRR abs/2401.00713 (2024) - [i29]Yifang Qin, Wei Ju, Xiao Luo, Yiyang Gu, Zhiping Xiao, Ming Zhang:
PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering. CoRR abs/2401.12590 (2024) - [i28]Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang:
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling. CoRR abs/2401.16011 (2024) - [i27]Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, Ming Zhang:
A Survey of Data-Efficient Graph Learning. CoRR abs/2402.00447 (2024) - [i26]Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang:
COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting. CoRR abs/2403.01091 (2024) - [i25]Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang:
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges. CoRR abs/2403.04468 (2024) - [i24]Wei Ju, Zhengyang Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang:
Hypergraph-enhanced Dual Semi-supervised Graph Classification. CoRR abs/2405.04773 (2024) - [i23]Wei Ju, Yifan Wang, Yifang Qin, Zhengyang Mao, Zhiping Xiao, Junyu Luo, Junwei Yang, Yiyang Gu, Dongjie Wang, Qingqing Long, Siyu Yi, Xiao Luo, Ming Zhang:
Towards Graph Contrastive Learning: A Survey and Beyond. CoRR abs/2405.11868 (2024) - [i22]Jinsheng Huang, Liang Chen, Taian Guo, Fu Zeng, Yusheng Zhao, Bohan Wu, Ye Yuan, Haozhe Zhao, Zhihui Guo, Yichi Zhang, Jingyang Yuan, Wei Ju, Luchen Liu, Tianyu Liu, Baobao Chang, Ming Zhang:
MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation. CoRR abs/2407.00468 (2024) - [i21]Yifan Wang, Xiao Luo, Chong Chen, Xian-Sheng Hua, Ming Zhang, Wei Ju:
DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning. CoRR abs/2407.14081 (2024) - [i20]Junyu Luo, Zhiping Xiao, Yifan Wang, Xiao Luo, Jingyang Yuan, Wei Ju, Langechuan Liu, Ming Zhang:
Rank and Align: Towards Effective Source-free Graph Domain Adaptation. CoRR abs/2408.12185 (2024) - 2023
- [j13]Wei Ju, Yiyang Gu, Xiao Luo, Yifan Wang, Haochen Yuan, Huasong Zhong, Ming Zhang:
Unsupervised graph-level representation learning with hierarchical contrasts. Neural Networks 158: 359-368 (2023) - [j12]Wei Ju, Zequn Liu, Yifang Qin, Bin Feng, Chen Wang, Zhihui Guo, Xiao Luo, Ming Zhang:
Few-shot Molecular Property Prediction via Hierarchically Structured Learning on Relation Graphs. Neural Networks 163: 122-131 (2023) - [j11]Siyu Yi, Zhengyang Mao, Wei Ju, Yong-Dao Zhou, Luchen Liu, Xiao Luo, Ming Zhang:
Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts. IEEE Trans. Big Data 9(6): 1683-1696 (2023) - [j10]Xiao Luo, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun:
RIGNN: A Rationale Perspective for Semi-supervised Open-world Graph Classification. Trans. Mach. Learn. Res. 2023 (2023) - [j9]Wei Ju, Yifang Qin, Siyu Yi, Zhengyang Mao, Kangjie Zheng, Luchen Liu, Xiao Luo, Ming Zhang:
Zero-shot Node Classification with Graph Contrastive Embedding Network. Trans. Mach. Learn. Res. 2023 (2023) - [j8]Xindi Wang, Xinyu Liu, Jianjian Wu, Wei Ju, Xiaojing Chen, Ling Shen:
Joint User Scheduling, Power Configuration and Trajectory Planning Strategy for UAV-Aided WSNs. ACM Trans. Sens. Networks 19(1): 10:1-10:27 (2023) - [c18]Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang:
GLCC: A General Framework for Graph-Level Clustering. AAAI 2023: 4391-4399 - [c17]Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang:
Learning on Graphs under Label Noise. ICASSP 2023: 1-5 - [c16]Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang:
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting. ICDE 2023: 2303-2316 - [c15]Xiao Luo, Jingyang Yuan, Zijie Huang, Huiyu Jiang, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun:
HOPE: High-order Graph ODE For Modeling Interacting Dynamics. ICML 2023: 23124-23139 - [c14]Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang:
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels. ACM Multimedia 2023: 3647-3656 - [c13]Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang:
RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification. ACM Multimedia 2023: 3817-3826 - [c12]Wei Ju, Aidan McConnell-Trevillion, Sadeque Reza Khan, Kianoush Nazarpour, Srinjoy Mitra:
A Feasibility Study on Textile Electrodes for Transcutaneous Electrical Nerve Stimulation. NEWCAS 2023: 1-5 - [c11]Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang:
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation. WSDM 2023: 508-516 - [i19]Bin Feng, Tenglong Ao, Zequn Liu, Wei Ju, Libin Liu, Ming Zhang:
Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data. CoRR abs/2303.16856 (2023) - [i18]Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Xiao Luo, Ming Zhang:
A Comprehensive Survey on Deep Graph Representation Learning. CoRR abs/2304.05055 (2023) - [i17]Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang:
A Diffusion model for POI recommendation. CoRR abs/2304.07041 (2023) - [i16]Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang:
Learning Graph ODE for Continuous-Time Sequential Recommendation. CoRR abs/2304.07042 (2023) - [i15]Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
TGNN: A Joint Semi-supervised Framework for Graph-level Classification. CoRR abs/2304.11688 (2023) - [i14]Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang:
Towards Semi-supervised Universal Graph Classification. CoRR abs/2305.19598 (2023) - [i13]Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang:
Learning on Graphs under Label Noise. CoRR abs/2306.08194 (2023) - [i12]Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang:
RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification. CoRR abs/2308.02335 (2023) - [i11]Siyu Yi, Zhengyang Mao, Wei Ju, Yongdao Zhou, Luchen Liu, Xiao Luo, Ming Zhang:
Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts. CoRR abs/2308.16609 (2023) - [i10]Chengwu Liu, Jianhao Shen, Huajian Xin, Zhengying Liu, Ye Yuan, Haiming Wang, Wei Ju, Chuanyang Zheng, Yichun Yin, Lin Li, Ming Zhang, Qun Liu:
FIMO: A Challenge Formal Dataset for Automated Theorem Proving. CoRR abs/2309.04295 (2023) - [i9]Siyu Yi, Wei Ju, Yifang Qin, Xiao Luo, Luchen Liu, Yong-Dao Zhou, Ming Zhang:
Redundancy-Free Self-Supervised Relational Learning for Graph Clustering. CoRR abs/2309.04694 (2023) - [i8]Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang:
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting. CoRR abs/2309.12028 (2023) - [i7]Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang:
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels. CoRR abs/2309.14673 (2023) - [i6]Xiao Luo, Yiyang Gu, Huiyu Jiang, Jinsheng Huang, Wei Ju, Ming Zhang, Yizhou Sun:
Graph ODE with Factorized Prototypes for Modeling Complicated Interacting Dynamics. CoRR abs/2311.06554 (2023) - 2022
- [j7]Tao Wang, Changhua Lu, Wei Ju, Chun Liu:
Imbalanced heartbeat classification using EasyEnsemble technique and global heartbeat information. Biomed. Signal Process. Control. 71(Part): 103105 (2022) - [j6]Xueyan Zhang, Xiaohu Zhou, Qiao Wang, Hui Zhang, Wei Ju:
Networks open the door to the success of technological entrepreneurship: a perspective on political skills. Kybernetes 51(12): 3487-3507 (2022) - [j5]Wei Ju, Xiao Luo, Zeyu Ma, Junwei Yang, Minghua Deng, Ming Zhang:
GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification. Neural Networks 151: 70-79 (2022) - [c10]Yifan Wang, Yiping Song, Shuai Li, Chaoran Cheng, Wei Ju, Ming Zhang, Sheng Wang:
DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation. AAAI 2022: 11449-11458 - [c9]Xiao Luo, Wei Ju, Meng Qu, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
DualGraph: Improving Semi-supervised Graph Classification via Dual Contrastive Learning. ICDE 2022: 699-712 - [c8]Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang:
Kernel-based Substructure Exploration for Next POI Recommendation. ICDM 2022: 221-230 - [c7]Yiping Song, Wei Ju, Zhiliang Tian, Luchen Liu, Ming Zhang, Zheng Xie:
Building Conversational Diagnosis Systems for Fine-Grained Diseases Using Few Annotated Data. ICONIP (3) 2022: 591-603 - [c6]Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang:
TGNN: A Joint Semi-supervised Framework for Graph-level Classification. IJCAI 2022: 2122-2128 - [c5]Zeyu Ma, Wei Ju, Xiao Luo, Chong Chen, Xian-Sheng Hua, Guangming Lu:
Improved Deep Unsupervised Hashing via Prototypical Learning. ACM Multimedia 2022: 659-667 - [c4]Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang:
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification. WSDM 2022: 421-429 - [i5]Wei Ju, Junwei Yang, Meng Qu, Weiping Song, Jianhao Shen, Ming Zhang:
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification. CoRR abs/2205.10550 (2022) - [i4]Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang:
Kernel-based Substructure Exploration for Next POI Recommendation. CoRR abs/2210.03969 (2022) - [i3]Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang:
GLCC: A General Framework for Graph-level Clustering. CoRR abs/2210.11879 (2022) - [i2]Yifang Qin, Yifan Wang, Fang Sun, Wei Ju, Xuyang Hou, Zhe Wang, Jia Cheng, Jun Lei, Ming Zhang:
DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation. CoRR abs/2210.16591 (2022) - 2021
- [c3]Xiao Luo, Yuhang Guo, Zeyu Ma, Huasong Zhong, Tao Li, Wei Ju, Chong Chen, Minghua Deng:
Deep Supervised Hashing by Classification for Image Retrieval. ICONIP (4) 2021: 3-14 - [c2]Weinan Wang, Yuhang Guo, Wei Ju, Xiao Luo, Minghua Deng:
An Interpretation of Convolutional Neural Networks for Motif Finding from the View of Probability. ICTAI 2021: 176-183 - [i1]Wei Ju, Wenxin Jiang:
A Note on Comparison of F-measures. CoRR abs/2112.04677 (2021) - 2020
- [j4]Feng Hong, Changhua Lu, Chun Liu, Ru-Ru Liu, Weiwei Jiang, Wei Ju, Tao Wang:
PGNet: Pipeline Guidance for Human Key-Point Detection. Entropy 22(3): 369 (2020)
2010 – 2019
- 2017
- [j3]Ivica Kopriva, Wei Ju, Bin Zhang, Fei Shi, Dehui Xiang, Kai Yu, Ximing Wang, Ulas Bagci, Xinjian Chen:
Single-Channel Sparse Non-Negative Blind Source Separation Method for Automatic 3-D Delineation of Lung Tumor in PET Images. IEEE J. Biomed. Health Informatics 21(6): 1656-1666 (2017) - 2016
- [j2]Wei Ju, Dehui Xiang, Bin Zhang, Lirong Wang, Ivica Kopriva, Xinjian Chen:
Correction to "Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images". IEEE Trans. Image Process. 25(3): 1192 (2016) - 2015
- [j1]Wei Ju, Deihui Xiang, Bin Zhang, Lirong Wang, Ivica Kopriva, Xinjian Chen:
Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images. IEEE Trans. Image Process. 24(12): 5854-5867 (2015) - [c1]Wei Ju, Dehui Xiang, Bin Zhang, Xinjian Chen:
Graph cut based co-segmentation of lung tumor in PET-CT images. Medical Imaging: Image Processing 2015: 94133K
Coauthor Index
[j22] [j21] [j20] [j19] [j18] [j17] [j16] [j15] [j14] [c22] [c21] [c20] [i30] [i29] [i28] [i26] [i25] [i24] [i23] [i21] [i20] [j13] [j12] [j11] [j10] [j9] [c18] [c17] [c16] [c15] [c14] [c13] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i9] [i8] [i7] [i6] [j5] [c9] [c8] [c6] [c5] [i4] [i3] [c3] [c2]
[j22] [j21] [j20] [j19] [j18] [j17] [j16] [j15] [j14] [c24] [c22] [c21] [c20] [c19] [i30] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i21] [i20] [j13] [j12] [j11] [j10] [j9] [c18] [c17] [c16] [c15] [c14] [c13] [c11] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [j5] [c10] [c9] [c8] [c7] [c6] [c4] [i5] [i4] [i3] [i2]
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