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ORCIDLifang He 0001
何丽芳
Person information
- affiliation: Lehigh University, Bethlehem, PA, USA
- affiliation: University of Pennsylvania, Department of Biostatistics, Epidemiology and Informatics, Philadelphia, PA, USA
- affiliation (former): Cornell University, Weill Cornell Medical College, New York, NY, USA
- affiliation (former): Shenzhen University, School of Computer Science and Software Engineering, Computer Vision Institute, China
- affiliation (PhD 2014): South China Institute of Technology, School of Computer Science and Engineering, Guangzhou, China
- unicode name: 何丽芳
Other persons with the same name
- Lifang He 0002 — Central South University, School of Information Science and Engineering, Changsha, China
- Lifang He 0003 — Nanjing University of Aeronautics and Astronautics, College of Economics and Management, China
- Lifang He 0004
![[0000-0002-0014-1845]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-0014-1845")
— Kunming University of Science and Technology, Department of Electronics and Communication Engineering, China - Lifang He 0005 — Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, China
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2020 – today
- 2024
[j44]Xinqi Du, Hechang Chen, Yongheng Xing, Philip S. Yu, Lifang He:
A Contrastive-Enhanced Ensemble Framework for Efficient Multi-Agent Reinforcement Learning. Expert Syst. Appl. 245: 123158 (2024)- [j43]Yazhou Ren, Xinyue Chen, Jie Xu, Jingyu Pu, Yonghao Huang, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He:
A novel federated multi-view clustering method for unaligned and incomplete data fusion. Inf. Fusion 108: 102357 (2024) - [j42]Xinqi Du, Hechang Chen, Che Wang, Yongheng Xing, Jielong Yang, Philip S. Yu, Yi Chang, Lifang He:
Robust multi-agent reinforcement learning via Bayesian distributional value estimation. Pattern Recognit. 145: 109917 (2024) - [j41]Jun Yu, Zhaoming Kong, Kun Chen, Xin Zhang, Yong Chen, Lifang He:
A Multilinear Least-Squares Formulation for Sparse Tensor Canonical Correlation Analysis. Trans. Mach. Learn. Res. 2024 (2024) - [j40]Song Wu, Yan Zheng, Yazhou Ren, Jing He, Xiaorong Pu, Shudong Huang, Zhifeng Hao, Lifang He:
Self-Weighted Contrastive Fusion for Deep Multi-View Clustering. IEEE Trans. Multim. 26: 9150-9162 (2024) - [j39]Haonan Huang, Guoxu Zhou, Qibin Zhao, Lifang He, Shengli Xie:
Comprehensive Multiview Representation Learning via Deep Autoencoder-Like Nonnegative Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. 35(5): 5953-5967 (2024) - [c91]Jingyu Pu, Chenhang Cui, Xinyue Chen, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He:
Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering. AAAI 2024: 14633-14641 - [c90]Zichen Wen, Yawen Ling, Yazhou Ren, Tianyi Wu, Jianpeng Chen, Xiaorong Pu, Zhifeng Hao, Lifang He:
Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering. AAAI 2024: 15841-15849 - [c89]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c88]JunLong Ke, Zichen Wen, Yechenhao Yang, Chenhang Cui, Yazhou Ren, Xiaorong Pu, Lifang He:
Integrating Vision-Language Semantic Graphs in Multi-View Clustering. IJCAI 2024: 4273-4281 - [c87]Yazhou Ren, Jingyu Pu, Chenhang Cui, Yan Zheng, Xinyue Chen, Xiaorong Pu, Lifang He:
Dynamic Weighted Graph Fusion for Deep Multi-View Clustering. IJCAI 2024: 4842-4850 - [c86]Yan Zheng, Song Wu, Junyu Lin, Yazhou Ren, Jing He, Xiaorong Pu, Lifang He:
Cross-View Contrastive Fusion for Enhanced Molecular Property Prediction. IJCAI 2024: 5617-5625 - [c85]Haoteng Tang, Guodong Liu, Siyuan Dai, Kai Ye, Kun Zhao, Wenlu Wang, Carl Yang, Lifang He, Alex D. Leow, Paul M. Thompson, Heng Huang, Liang Zhan:
Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation. MICCAI (2) 2024: 227-237 - [c84]Zichen Wen, Tianyi Wu, Yazhou Ren, Yawen Ling, Chenhang Cui, Xiaorong Pu, Lifang He:
Dual-Optimized Adaptive Graph Reconstruction for Multi-View Graph Clustering. ACM Multimedia 2024: 1819-1828 - [c83]Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Runze Yang, Chunyang Liu, Lifang He:
Semi-Supervised Clustering via Structural Entropy with Different Constraints. SDM 2024: 208-216 - [i82]Zichen Wen, Yawen Ling, Yazhou Ren, Tianyi Wu, Jianpeng Chen, Xiaorong Pu, Zhifeng Hao, Lifang He:
Homophily-Related: Adaptive Hybrid Graph Filter for Multi-View Graph Clustering. CoRR abs/2401.02682 (2024) - [i81]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i80]Yixin Liu, Kai Zhang, Yuan Li, Zhiling Yan, Chujie Gao, Ruoxi Chen, Zhengqing Yuan, Yue Huang, Hanchi Sun, Jianfeng Gao, Lifang He, Lichao Sun:
Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models. CoRR abs/2402.17177 (2024) - [i79]Zhengqing Yuan, Ruoxi Chen, Zhaoxu Li, Haolong Jia, Lifang He, Chi Wang, Lichao Sun:
Mora: Enabling Generalist Video Generation via A Multi-Agent Framework. CoRR abs/2403.13248 (2024) - [i78]Kaiqiao Han, Yi Yang, Zijie Huang, Xuan Kan, Yang Yang, Ying Guo, Lifang He, Liang Zhan, Yizhou Sun, Wei Wang, Carl Yang:
BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations. CoRR abs/2405.00077 (2024) - [i77]Haoteng Tang, Guodong Liu, Siyuan Dai, Kai Ye, Kun Zhao, Wenlu Wang, Carl Yang, Lifang He, Alex D. Leow, Paul Thompson, Heng Huang, Liang Zhan:
Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation. CoRR abs/2405.13190 (2024) - [i76]Zhengqing Yuan, Rong Zhou, Hongyi Wang, Lifang He, Yanfang Ye, Lichao Sun:
ViT-1.58b: Mobile Vision Transformers in the 1-bit Era. CoRR abs/2406.18051 (2024) - [i75]Weixiang Sun, Xiaocao You, Ruizhe Zheng, Zhengqing Yuan, Xiang Li, Lifang He, Quanzheng Li, Lichao Sun:
Bora: Biomedical Generalist Video Generation Model. CoRR abs/2407.08944 (2024) - [i74]Zhiling Yan, Weixiang Sun, Rong Zhou, Zhengqing Yuan, Kai Zhang, Yiwei Li, Tianming Liu, Quanzheng Li, Xiang Li, Lifang He, Lichao Sun:
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos. CoRR abs/2408.03286 (2024) - [i73]Rong Zhou, Zhengqing Yuan, Zhiling Yan, Weixiang Sun, Kai Zhang, Yiwei Li, Yanfang Ye, Xiang Li, Lifang He, Lichao Sun:
TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation. CoRR abs/2409.11299 (2024) - [i72]Jianpeng Chen, Yawen Ling, Yazhou Ren, Zichen Wen, Tianyi Wu, Shufei Zhang, Lifang He:
SiMilarity-Enhanced Homophily for Multi-View Heterophilous Graph Clustering. CoRR abs/2410.03596 (2024) - [i71]Zichen Wen, Tianyi Wu, Yazhou Ren, Yawen Ling, Chenhang Cui, Xiaorong Pu, Lifang He:
Dual-Optimized Adaptive Graph Reconstruction for Multi-View Graph Clustering. CoRR abs/2410.22983 (2024) - 2023
- [j38]Zhimeng Yang, Yazhou Ren, Zirui Wu, Ming Zeng, Jie Xu, Yang Yang, Xiaorong Pu, Philip S. Yu, Lifang He:
DC-FUDA: Improving deep clustering via fully unsupervised domain adaptation. Neurocomputing 526: 109-120 (2023) - [j37]Yucheng Jin, Yun Xiong, Dan Shi, Yifei Lin, Lifang He, Yao Zhang, Joseph M. Plasek, Li Zhou, David W. Bates, Chunlei Tang:
Learning from undercoded clinical records for automated International Classification of Diseases (ICD) coding. J. Am. Medical Informatics Assoc. 30(3): 438-446 (2023) - [j36]Feng Zhao, Cheng Yan, Hai Jin, Lifang He:
BayesKGR: Bayesian Few-Shot Learning for Knowledge Graph Reasoning. ACM Trans. Asian Low Resour. Lang. Inf. Process. 22(6): 160:1-160:21 (2023) - [j35]Jianxin Li, Hao Peng, Yuwei Cao, Yingtong Dou, Hekai Zhang, Philip S. Yu, Lifang He:
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(1): 560-574 (2023) - [j34]Hao Peng, Jianxin Li, Zheng Wang, Renyu Yang, Mingsheng Liu, Mingming Zhang, Philip S. Yu, Lifang He:
Lifelong Property Price Prediction: A Case Study for the Toronto Real Estate Market. IEEE Trans. Knowl. Data Eng. 35(3): 2765-2780 (2023) - [j33]Jie Xu, Yazhou Ren, Huayi Tang, Zhimeng Yang, Lili Pan, Yang Yang, Xiaorong Pu, Philip S. Yu, Lifang He:
Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 35(7): 7470-7482 (2023) - [j32]Lichao Sun, Yingtong Dou, Carl Yang, Kai Zhang, Ji Wang, Philip S. Yu, Lifang He, Bo Li:
Adversarial Attack and Defense on Graph Data: A Survey. IEEE Trans. Knowl. Data Eng. 35(8): 7693-7711 (2023) - [j31]Jianxin Li, Xingcheng Fu, Shijie Zhu, Hao Peng, Senzhang Wang, Qingyun Sun, Philip S. Yu, Lifang He:
A Robust and Generalized Framework for Adversarial Graph Embedding. IEEE Trans. Knowl. Data Eng. 35(11): 11004-11018 (2023) - [j30]Jianxin Li, Lifang He, Hao Peng, Peng Cui, Charu C. Aggarwal, Philip S. Yu:
Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and Applications. IEEE Trans. Knowl. Data Eng. 35(12): 11982-11983 (2023) - [j29]Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang:
BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks. IEEE Trans. Medical Imaging 42(2): 493-506 (2023) - [c82]Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu, Lifang He:
Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering. AAAI 2023: 7936-7943 - [c81]Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He:
Dual Label-Guided Graph Refinement for Multi-View Graph Clustering. AAAI 2023: 8791-8798 - [c80]Houliang Zhou, Yu Zhang, Lifang He, Li Shen, Brian Y. Chen:
Interpretable Graph Convolutional Network for Alzheimer's Disease Diagnosis using Multi-Modal Imaging Genetics. BIBM 2023: 1004-1007 - [c79]Rong Zhou, Houliang Zhou, Li Shen, Brian Y. Chen, Yu Zhang, Lifang He:
Integrating Multimodal Contrastive Learning and Cross-Modal Attention for Alzheimer's Disease Prediction in Brain Imaging Genetics. BIBM 2023: 1806-1811 - [c78]Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He:
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. ICDM 2023: 768-777 - [c77]Chenhang Cui, Yazhou Ren, Jingyu Pu, Xiaorong Pu, Lifang He:
Deep Multi-view Subspace Clustering with Anchor Graph. IJCAI 2023: 3577-3585 - [c76]Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu:
Hierarchical State Abstraction based on Structural Information Principles. IJCAI 2023: 4549-4557 - [c75]Xuetong Wang, Rong Zhou, Kanhao Zhao, Alex D. Leow, Yu Zhang, Lifang He:
Normative Modeling Via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease. ISBI 2023: 1-4 - [c74]Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong:
One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. KDD 2023: 2049-2060 - [c73]Rong Zhou, Houliang Zhou, Brian Y. Chen, Li Shen, Yu Zhang, Lifang He:
Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer's Disease Using Multimodal Imaging Genetics. MICCAI (2) 2023: 681-691 - [c72]Xinyue Chen, Jie Xu, Yazhou Ren, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He:
Federated Deep Multi-View Clustering with Global Self-Supervision. ACM Multimedia 2023: 3498-3506 - [c71]Zhenqian Wu, Yazhou Ren, Xiaorong Pu, Zhifeng Hao, Lifang He:
Generative Neutral Features-Disentangled Learning for Facial Expression Recognition. ACM Multimedia 2023: 4300-4308 - [c70]Chenhang Cui, Yazhou Ren, Jingyu Pu, Jiawei Li, Xiaorong Pu, Tianyi Wu, Yutao Shi, Lifang He:
A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective. NeurIPS 2023 - [i70]Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun:
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT. CoRR abs/2302.09419 (2023) - [i69]Zhenqian Wu, Xiaoyuan Li, Yazhou Ren, Xiaorong Pu, Xiaofeng Zhu, Lifang He:
Self-Paced Neutral Expression-Disentangled Learning for Facial Expression Recognition. CoRR abs/2303.11840 (2023) - [i68]Zhaoming Kong, Fangxi Deng, Haomin Zhuang, Xiaowei Yang, Jun Yu, Lifang He:
A Comparison of Image Denoising Methods. CoRR abs/2304.08990 (2023) - [i67]Xianghua Zeng, Hao Peng, Angsheng Li, Chunyang Liu, Lifang He, Philip S. Yu:
Hierarchical State Abstraction Based on Structural Information Principles. CoRR abs/2304.12000 (2023) - [i66]Chenhang Cui, Yazhou Ren, Jingyu Pu, Xiaorong Pu, Lifang He:
Deep Multi-View Subspace Clustering with Anchor Graph. CoRR abs/2305.06939 (2023) - [i65]Kai Zhang, Jun Yu, Zhiling Yan, Yixin Liu, Eashan Adhikarla, Sunyang Fu, Xun Chen, Chen Chen, Yuyin Zhou, Xiang Li, Lifang He, Brian D. Davison, Quanzheng Li, Yong Chen, Hongfang Liu, Lichao Sun:
BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks. CoRR abs/2305.17100 (2023) - [i64]Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong:
One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data. CoRR abs/2307.15198 (2023) - [i63]Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Chunyang Liu, Philip S. Yu, Lifang He:
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs. CoRR abs/2309.01899 (2023) - [i62]Xinyue Chen, Jie Xu, Yazhou Ren, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He:
Federated Deep Multi-View Clustering with Global Self-Supervision. CoRR abs/2309.13697 (2023) - [i61]Chenhang Cui, Yazhou Ren, Jingyu Pu, Jiawei Li, Xiaorong Pu, Tianyi Wu, Yutao Shi, Lifang He:
A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective. CoRR abs/2309.13989 (2023) - [i60]Zhiling Yan, Kai Zhang, Rong Zhou, Lifang He, Xiang Li, Lichao Sun:
Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V. CoRR abs/2310.19061 (2023) - [i59]Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Runze Yang, Chunyang Liu, Lifang He:
Semi-Supervised Clustering via Structural Entropy with Different Constraints. CoRR abs/2312.10917 (2023) - 2022
- [j28]Yue Fei, Fan Chen, Lifang He, Jiamin Chen, Yuexing Hao, Xia Li, Guiqing Liu, Qinqun Chen, Li Li, Hang Wei:
Intelligent classification of antenatal cardiotocography signals via multimodal bidirectional gated recurrent units. Biomed. Signal Process. Control. 78: 104008 (2022) - [j27]Hongren Huang, Chen Li, Xutan Peng, Lifang He, Shu Guo, Hao Peng, Lihong Wang, Jianxin Li:
Cross-knowledge-graph entity alignment via relation prediction. Knowl. Based Syst. 240: 107813 (2022) - [j26]Liping Huang, Yongjian Yang, Hechang Chen, Yunke Zhang, Zijia Wang, Lifang He:
Context-aware road travel time estimation by coupled tensor decomposition based on trajectory data. Knowl. Based Syst. 245: 108596 (2022) - [j25]Xiangchun Yu, Hechang Chen, Miaomiao Liang, Qing Xu, Lifang He:
A transfer learning-based novel fusion convolutional neural network for breast cancer histology classification. Multim. Tools Appl. 81(9): 11949-11963 (2022) - [j24]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica J. M. Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep reinforcement learning guided graph neural networks for brain network analysis. Neural Networks 154: 56-67 (2022) - [j23]Hao Peng, Renyu Yang, Zheng Wang, Jianxin Li, Lifang He, Philip S. Yu, Albert Y. Zomaya, Rajiv Ranjan:
Lime: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks. IEEE Trans. Computers 71(3): 628-642 (2022) - [j22]Xiaohang Xu, Hao Peng, Md. Zakirul Alam Bhuiyan, Zhifeng Hao, Lianzhong Liu, Lichao Sun, Lifang He:
Privacy-Preserving Federated Depression Detection From Multisource Mobile Health Data. IEEE Trans. Ind. Informatics 18(7): 4788-4797 (2022) - [j21]Qian Li, Hao Peng, Jianxin Li, Congying Xia, Renyu Yang, Lichao Sun, Philip S. Yu, Lifang He:
A Survey on Text Classification: From Traditional to Deep Learning. ACM Trans. Intell. Syst. Technol. 13(2): 31:1-31:41 (2022) - [j20]Sicong Che, Zhaoming Kong, Hao Peng, Lichao Sun, Alex D. Leow, Yong Chen, Lifang He:
Federated Multi-view Learning for Private Medical Data Integration and Analysis. ACM Trans. Intell. Syst. Technol. 13(4): 61:1-61:23 (2022) - [j19]Chen Li, Hao Peng, Jianxin Li, Lichao Sun, Lingjuan Lyu, Lihong Wang, Philip S. Yu, Lifang He:
Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2530-2542 (2022) - [c69]Gongxu Luo, Chenyang Li, Hejie Cui, Lichao Sun, Lifang He, Carl Yang:
Multi-View Brain Network Analysis with Cross-View Missing Network Generation. BIBM 2022: 108-115 - [c68]Jun Yu, Benjamin Zalatan, Yong Chen, Li Shen, Lifang He:
Tensor-Based Multi-Modal Multi-Target Regression for Alzheimer's Disease Prediction. BIBM 2022: 639-646 - [c67]Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang:
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks (Extended Abstract). IEEE Big Data 2022: 4968-4969 - [c66]Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He:
From Known to Unknown: Quality-aware Self-improving Graph Neural Network For Open Set Social Event Detection. CIKM 2022: 1696-1705 - [c65]Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He:
Multi-level Feature Learning for Contrastive Multi-view Clustering. CVPR 2022: 16030-16039 - [c64]Yanqiao Zhu, Hejie Cui, Lifang He, Lichao Sun, Carl Yang:
Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis. EMBC 2022: 272-276 - [c63]Yao Su, Xin Dai, Lifang He, Xiangnan Kong:
ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. ICDM 2022: 468-477 - [c62]Jianpeng Chen, Zhimeng Yang, Jingyu Pu, Yazhou Ren, Xiaorong Pu, Li Gao, Lifang He:
Shared-Attribute Multi-Graph Clustering with Global Self-Attention. ICONIP (1) 2022: 51-63 - [c61]Jun Yu, Zhaoming Kong, Aditya Kendre, Hao Peng, Carl Yang, Lichao Sun, Alex D. Leow, Lifang He:
Structure-Preserving Graph Kernel for Brain Network Classification. ISBI 2022: 1-5 - [c60]Houliang Zhou, Lifang He, Yu Zhang, Li Shen, Brian Chen:
Interpretable Graph Convolutional Network Of Multi-Modality Brain Imaging For Alzheimer's Disease Diagnosis. ISBI 2022: 1-5 - [c59]Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong:
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. KDD 2022: 1666-1675 - [c58]Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang:
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. KDD 2022: 4743-4751 - [c57]Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang:
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis. MICCAI (8) 2022: 375-385 - [c56]Houliang Zhou, Yu Zhang, Brian Y. Chen, Li Shen, Lifang He:
Sparse Interpretation of Graph Convolutional Networks for Multi-modal Diagnosis of Alzheimer's Disease. MICCAI (8) 2022: 469-478 - [i58]Weihang Yuan, Hector Muñoz-Avila, Venkatsampath Raja Gogineni, Sravya Kondrakunta, Michael T. Cox, Lifang He:
Task Modifiers for HTN Planning and Acting. CoRR abs/2202.04611 (2022) - [i57]Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Philip S. Yu, Lifang He, Ruth Nussinov, Feixiong Cheng:
Deep learning for drug repurposing: methods, databases, and applications. CoRR abs/2202.05145 (2022) - [i56]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep Reinforcement Learning Guided Graph Neural Networks for Brain Network Analysis. CoRR abs/2203.10093 (2022) - [i55]Hejie Cui, Wei Dai, Yanqiao Zhu, Xuan Kan, Antonio Aodong Chen Gu, Joshua Lukemire, Liang Zhan, Lifang He, Ying Guo, Carl Yang:
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks. CoRR abs/2204.07054 (2022) - [i54]Houliang Zhou, Lifang He, Yu Zhang, Li Shen, Brian Chen:
Interpretable Graph Convolutional Network of Multi-Modality Brain Imaging for Alzheimer's Disease Diagnosis. CoRR abs/2204.13188 (2022) - [i53]Zongmo Huang, Yazhou Ren, Xiaorong Pu, Lifang He:
Deep Embedded Multi-View Clustering via Jointly Learning Latent Representations and Graphs. CoRR abs/2205.03803 (2022) - [i52]Yi Yang, Yanqiao Zhu, Hejie Cui, Xuan Kan, Lifang He, Ying Guo, Carl Yang:
Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning. CoRR abs/2206.04486 (2022) - [i51]Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang:
Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis. CoRR abs/2207.00813 (2022) - [i50]Jiaqian Ren, Lei Jiang, Hao Peng, Yuwei Cao, Jia Wu, Philip S. Yu, Lifang He:
From Known to Unknown: Quality-aware Self-improving Graph Neural Network for Open Set Social Event Detection. CoRR abs/2208.06973 (2022) - [i49]Jun Yu, Zhaoming Kong, Liang Zhan, Li Shen, Lifang He:
Tensor-Based Multi-Modality Feature Selection and Regression for Alzheimer's Disease Diagnosis. CoRR abs/2209.11372 (2022) - [i48]Yazhou Ren, Jingyu Pu, Zhimeng Yang, Jie Xu, Guofeng Li, Xiaorong Pu, Philip S. Yu, Lifang He:
Deep Clustering: A Comprehensive Survey. CoRR abs/2210.04142 (2022) - [i47]Jianpeng Chen, Yawen Ling, Jie Xu, Yazhou Ren, Shudong Huang, Xiaorong Pu, Lifang He:
Variational Graph Generator for Multi-View Graph Clustering. CoRR abs/2210.07011 (2022) - [i46]Xuetong Wang, Kanhao Zhao, Rong Zhou, Alex D. Leow, Ricardo Osorio, Yu Zhang, Lifang He:
Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease. CoRR abs/2211.08982 (2022) - [i45]Yao Su, Xin Dai, Lifang He, Xiangnan Kong:
ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration. CoRR abs/2212.03277 (2022) - [i44]Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong:
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data. CoRR abs/2212.03306 (2022) - 2021
- [j18]Hao Peng, Bowen Du, Mingsheng Liu, Mingzhe Liu, Shumei Ji, Senzhang Wang, Xu Zhang, Lifang He:
Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning. Inf. Sci. 578: 401-416 (2021) - [j17]Haoteng Tang, Guixiang Ma, Lifang He, Heng Huang, Liang Zhan:
CommPOOL: An interpretable graph pooling framework for hierarchical graph representation learning. Neural Networks 143: 669-677 (2021) - [j16]Hao Peng, Jianxin Li, Yangqiu Song, Renyu Yang, Rajiv Ranjan, Philip S. Yu, Lifang He:
Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks. ACM Trans. Knowl. Discov. Data 15(5): 89:1-89:33 (2021) - [j15]Hao Peng, Jianxin Li, Senzhang Wang, Lihong Wang, Qiran Gong, Renyu Yang, Bo Li, Philip S. Yu, Lifang He:
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. IEEE Trans. Knowl. Data Eng. 33(6): 2505-2519 (2021)