Genetic Algorithm with Local Search for Community Mining in Complex Networks. - Di Jin 001; Dongxiao He; Dayou Liu; Carlos Baquero (ICTAI (1), 2010)

Ant colony optimization for community detection in large-scale complex networks. - Dongxiao He; Jie Liu 014; Dayou Liu; Di Jin 001; Zhengxue Jia (ICNC, 2011)

Ant Colony Optimization with Markov Random Walk for Community Detection in Graphs. - Di Jin 001; Dayou Liu; Bo Yang 002; Carlos Baquero; Dongxiao He (PAKDD (2), 2011)

Ant Colony Optimization with a New Random Walk Model for Community Detection in Complex Networks. - Di Jin 001; Dayou Liu; Bo Yang 002; Jie Liu 014; Dongxiao He (Adv. Complex Syst., 2011)

An Ant-Based Algorithm with Local Optimization for Community Detection in Large-Scale Networks. - Dongxiao He; Jie Liu 014; Bo Yang 002; Yuxiao Huang; Dayou Liu; Di Jin 001 (Adv. Complex Syst., 2012)

Identification of hybrid node and link communities in complex networks. - Dongxiao He; Weixiong Zhang (CoRR, 2013)

Discovering link communities in complex networks by exploiting link dynamics - Dongxiao He; Dayou Liu; Weixiong Zhang; Di Jin 001; Bo Yang 002 (CoRR, 2013)

Genetic Algorithm with Ensemble Learning for Detecting Community Structure in Complex Networks - Dongxiao He; Zhe Wang 007; Bin Yang; Chunguang Zhou (CoRR, 2013)

Markov random walk under constraint for discovering overlapping communities in complex networks - Di Jin 001; Bo Yang 002; Carlos Baquero; Dayou Liu; Dongxiao He; Jie Liu 014 (CoRR, 2013)

Genetic Algorithm with a Local Search Strategy for Discovering Communities in Complex Networks. - Dayou Liu; Di Jin 001; Carlos Baquero; Dongxiao He; Bo Yang 002; Qiangyuan Yu (Int. J. Comput. Intell. Syst., 2013)

The (un)supervised detection of overlapping communities as well as hubs and outliers via (bayesian) NMF. - Xiaochun Cao; Xiao Wang 017; Di Jin 001; Yixin Cao 001; Dongxiao He (WWW (Companion Volume), 2014)

A Stochastic Model for Detecting Heterogeneous Link Communities in Complex Networks. - Dongxiao He; Dayou Liu; Di Jin 001; Weixiong Zhang (AAAI, 2015)

Modeling with Node Degree Preservation Can Accurately Find Communities. - Di Jin 001; Zheng Chen; Dongxiao He; Weixiong Zhang (AAAI, 2015)

Detect Overlapping Communities via Ranking Node Popularities. - Di Jin 001; Hongcui Wang; Jianwu Dang 001; Dongxiao He; Weixiong Zhang (AAAI, 2016)

Node-Grained Incremental Community Detection for Streaming Networks. - Siwen Yin; Shizhan Chen; Zhiyong Feng 002; Keman Huang; Dongxiao He; Peng Zhao; Michael Ying Yang (ICTAI, 2016)

Modularity Based Community Detection with Deep Learning. - Liang Yang 002; Xiaochun Cao; Dongxiao He; Chuan Wang 002; Xiao Wang 017; Weixiong Zhang (IJCAI, 2016)

Autonomous overlapping community detection in temporal networks: A dynamic Bayesian nonnegative matrix factorization approach. - Wenjun Wang 002; Pengfei Jiao; Dongxiao He; Di Jin 001; Lin Pan 002; Bogdan Gabrys (Knowl. Based Syst., 2016)

Joint Identification of Network Communities and Semantics via Integrative Modeling of Network Topologies and Node Contents. - Dongxiao He; Zhiyong Feng 002; Di Jin 001; Xiaobao Wang; Weixiong Zhang (AAAI, 2017)

Adaptive Community Detection Incorporating Topology and Content in Social Networks. - Meng Qin 002; Di Jin 001; Dongxiao He; Bogdan Gabrys; Katarzyna Musial (ASONAM, 2017)

Using Deep Learning for Community Discovery in Social Networks. - Di Jin 001; Meng Ge; Zhixuan Li; Wenhuan Lu; Dongxiao He; Françoise Fogelman-Soulié (ICTAI, 2017)

Identification of Generalized Communities with Semantics in Networks with Content. - Di Jin 001; Xiaobao Wang; Dongxiao He; Wenhuan Lu; Françoise Fogelman-Soulié; Jianwu Dang 001 (ICTAI, 2017)

Semi-supervised community detection based on non-negative matrix factorization with node popularity. - Xiao Liu; Wenjun Wang 002; Dongxiao He; Pengfei Jiao; Di Jin 001; Carlo Vittorio Cannistraci (Inf. Sci., 2017)

A Network-Specific Markov Random Field Approach to Community Detection. - Dongxiao He; Xinxin You; Zhiyong Feng 002; Di Jin 001; Xue Yang; Weixiong Zhang (AAAI, 2018)

Robust Detection of Link Communities in Large Social Networks by Exploiting Link Semantics. - Di Jin 001; Xiaobao Wang; Ruifang He; Dongxiao He; Jianwu Dang 001; Weixiong Zhang (AAAI, 2018)

Edge Content Enhanced Network Embedding. - Hongcui Wang; Erwei Wang; Di Jin 001; Xiao Wang 017; Jing Wang 023; Dongxiao He (ICTAI, 2018)

A Probabilistic Model for Service Clustering - Jointly Using Service Invocation and Service Characteristics. - Dongxiao He; Xue Yang; Zhiyong Feng 002; Shizhan Chen; Keman Huang; Zhenzhu Wang; Françoise Fogelman-Soulié (ICWS, 2018)

Integrative Network Embedding via Deep Joint Reconstruction. - Di Jin 001; Meng Ge; Liang Yang 002; Dongxiao He; Longbiao Wang; Weixiong Zhang (IJCAI, 2018)

Manifold-based incremental community detection method for online speaker identification. - Hongcui Wang; Dongxiao He; Jianwu Dang 001; Xi Liang 004 (ISCSLP, 2018)

A Network Embedding-Enhanced Approach for Generalized Community Detection. - Dongxiao He; Xue Yang; Zhiyong Feng 002; Shizhan Chen; Françoise Fogelman-Soulié (KSEM (2), 2018)

Quantifying the Emergence of New Domains: Using Cybersecurity as a Case. - Xiaoli Hu; Zhiyong Feng 002; Shizhan Chen; Dongxiao He; Keman Huang (KSEM (2), 2018)

Robust Detection of Communities with Multi-semantics in Large Attributed Networks. - Di Jin 001; Ziyang Liu 004; Dongxiao He; Bogdan Gabrys; Katarzyna Musial (KSEM (1), 2018)

Performance Analysis of MMSE Pre-Coding Aided Spatial Modulation. - You Li 003; Xia Lei; Wanbin Tang; Dongxiao He; Yue Xiao 001; Wei Xiang 001 (IEEE Access, 2018)

Performance Analysis for the N-Continuous Precoded SM-OFDM System. - Yue Xiao 001; Feng Yu; Xia Lei; Dongxiao He; Ping Yang 005; Wei Xiang 001 (IEEE Trans. Veh. Technol., 2018)

Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks. - Di Jin 001; Ziyang Liu 004; Weihao Li; Dongxiao He; Weixiong Zhang (AAAI, 2019)

Incorporating Network Embedding into Markov Random Field for Better Community Detection. - Di Jin 001; Xinxin You; Weihao Li; Dongxiao He; Peng Cui; Françoise Fogelman-Soulié; Tanmoy Chakraborty 002 (AAAI, 2019)

Emotional Contagion-Based Social Sentiment Mining in Social Networks by Introducing Network Communities. - Xiaobao Wang; Di Jin 001; Mengquan Liu; Dongxiao He; Katarzyna Musial; Jianwu Dang 001 (CIKM, 2019)

Community Detection via Joint Graph Convolutional Network Embedding in Attribute Network. - Di Jin 001; Bingyi Li; Pengfei Jiao; Dongxiao He; Hongyu Shan (ICANN (Workshop), 2019)

Adversarial Capsule Learning for Network Embedding. - Di Jin 001; Zhigang Li; Liang Yang 002; Dongxiao He; Pengfei Jiao; Lu Zhai (ICTAI, 2019)

An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph. - Dongxiao He; Wenze Song; Di Jin 001; Zhiyong Feng 002; Yuxiao Huang (IJCAI, 2019)

Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks. - Di Jin 001; Bingyi Li; Pengfei Jiao; Dongxiao He; Weixiong Zhang (IJCAI, 2019)

A Simple and Effective Community Detection Method Combining Network Topology with Node Attributes. - Dongxiao He; Yue Song; Di Jin 001 (KSEM (1), 2019)

A Novel Generative Topic Embedding Model by Introducing Network Communities. - Di Jin 001; Jiantao Huang; Pengfei Jiao; Liang Yang 002; Dongxiao He; Françoise Fogelman-Soulié; Yuxiao Huang (WWW, 2019)

Community-Centric Graph Convolutional Network for Unsupervised Community Detection. - Dongxiao He; Yue Song; Di Jin 001; Zhiyong Feng 002; Binbin Zhang; Zhizhi Yu; Weixiong Zhang (IJCAI, 2020)

Adversarial Mutual Information Learning for Network Embedding. - Dongxiao He; Lu Zhai; Zhigang Li; Di Jin 001; Liang Yang 002; Yuxiao Huang; Philip S. Yu (IJCAI, 2020)

ModMRF: A modularity-based Markov Random Field method for community detection. - Di Jin 001; Binbin Zhang; Yue Song; Dongxiao He; Zhiyong Feng 002; Shizhan Chen; Weihao Li; Katarzyna Musial (Neurocomputing, 2020)

Modeling with Node Popularities for Autonomous Overlapping Community Detection. - Di Jin 001; Bingyi Li; Pengfei Jiao; Dongxiao He; Hongyu Shan; Weixiong Zhang (ACM Trans. Intell. Syst. Technol., 2020)

Detecting Communities with Multiplex Semantics by Distinguishing Background, General, and Specialized Topics. - Di Jin 001; Kunzeng Wang; Ge Zhang 002; Pengfei Jiao; Dongxiao He; Françoise Fogelman-Soulié; Xin Huang 001 (IEEE Trans. Knowl. Data Eng., 2020)

AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks. - Zhizhi Yu; Di Jin 001; Ziyang Liu 004; Dongxiao He; Xiao Wang 017; Hanghang Tong; Jiawei Han 001 (ICDM, 2021)

Self-Guided Community Detection on Networks with Missing Edges. - Dongxiao He; Shuai Li; Di Jin 001; Pengfei Jiao; Yuxiao Huang (IJCAI, 2021)

HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization. - Zhongfen Deng; Hao Peng 001; Dongxiao He; Jianxin Li 002; Philip S. Yu (NAACL-HLT, 2021)

Universal Graph Convolutional Networks. - Di Jin 001; Zhizhi Yu; Cuiying Huo; Rui Wang 102; Xiao Wang 017; Dongxiao He; Jiawei Han 001 (NeurIPS, 2021)

Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily. - Tao Wang 074; Rui Wang 102; Di Jin 001; Dongxiao He; Yuxiao Huang (CoRR, 2021)

Semi-supervised community detection on attributed networks using non-negative matrix tri-factorization with node popularity. - Di Jin 001; Jing He; Bianfang Chai; Dongxiao He (Frontiers Comput. Sci., 2021)

Event prediction based on evolutionary event ontology knowledge. - Qianren Mao; Xi Li 001; Hao Peng 001; Jianxin Li 002; Dongxiao He; Shu Guo; Min He; Lihong Wang (Future Gener. Comput. Syst., 2021)

A network embedding-enhanced Bayesian model for generalized community detection in complex networks. - Dongxiao He; Youyou Wang; Jinxin Cao; Weiping Ding 001; Shizhan Chen; Zhiyong Feng 002; Bo Wang 011; Yuxiao Huang (Inf. Sci., 2021)

Robust Detection of Link Communities With Summary Description in Social Networks. - Di Jin 001; Xiaobao Wang; Dongxiao He; Jianwu Dang 001; Weixiong Zhang (IEEE Trans. Knowl. Data Eng., 2021)

Block Modeling-Guided Graph Convolutional Neural Networks. - Dongxiao He; Chundong Liang; Huixin Liu; Mingxiang Wen; Pengfei Jiao; Zhiyong Feng 002 (AAAI, 2022)

Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily. - Tao Wang 074; Di Jin 001; Rui Wang 102; Dongxiao He; Yuxiao Huang (AAAI, 2022)

Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing. - Liang Yang 002; Cheng Chen; Weixun Li; Bingxin Niu; Junhua Gu; Chuan Wang 002; Dongxiao He; Yuanfang Guo; Xiaochun Cao (AAAI, 2022)

RAW-GNN: RAndom Walk Aggregation based Graph Neural Network. - Di Jin 001; Rui Wang 102; Meng Ge; Dongxiao He; Xiang Li 067; Wei Lin 022; Weixiong Zhang (IJCAI, 2022)

Difference Residual Graph Neural Networks. - Liang Yang 002; Weihang Peng; Wenmiao Zhou; Bingxin Niu; Junhua Gu; Chuan Wang 002; Yuanfang Guo; Dongxiao He; Xiaochun Cao (ACM Multimedia, 2022)

OPEN: Orthogonal Propagation with Ego-Network Modeling. - Liang Yang 002; Lina Kang; Qiuliang Zhang; Mengzhe Li; Bingxin Niu; Dongxiao He; Zhen Wang 004; Chuan Wang 002; Xiaochun Cao; Yuanfang Guo (NeurIPS, 2022)

Graph Neural Networks Beyond Compromise Between Attribute and Topology. - Liang Yang 002; Wenmiao Zhou; Weihang Peng; Bingxin Niu; Junhua Gu; Chuan Wang 002; Xiaochun Cao; Dongxiao He (WWW, 2022)

Inflation Improves Graph Neural Networks. - Dongxiao He; Rui Guo; Xiaobao Wang; Di Jin 001; Yuxiao Huang; Wenjun Wang 002 (WWW, 2022)

Graph Neural Network for Higher-Order Dependency Networks. - Di Jin 001; Yingli Gong; Zhiqiang Wang; Zhizhi Yu; Dongxiao He; Yuxiao Huang; Wenjun Wang 002 (WWW, 2022)

Community Detection in Social Networks Considering Social Behaviors. - Yingkui Wang; Di Jin 001; Dongxiao He; Katarzyna Musial; Jianwu Dang 001 (IEEE Access, 2022)

A Joint Community Detection Model: Integrating Directed and Undirected Probabilistic Graphical Models via Factor Graph With Attention Mechanism. - Dongxiao He; Huixin Liu; Zhiyong Feng 002; Xiaobao Wang; Di Jin 001; Wenze Song; Yuxiao Huang (IEEE Trans. Big Data, 2022)

Identification of Communities With Multi-Semantics via Bayesian Generative Model. - Dongxiao He; Yanli Wu; Youyou Wang; Zhizhi Yu; Zhiyong Feng 002; Xiaobao Wang; Yuxiao Huang (IEEE Trans. Big Data, 2022)

Temporal Network Embedding for Link Prediction via VAE Joint Attention Mechanism. - Pengfei Jiao; Xuan Guo; Xin Jing; Dongxiao He; Huaming Wu; Shirui Pan; Maoguo Gong; Wenjun Wang 002 (IEEE Trans. Neural Networks Learn. Syst., 2022)

T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation. - Cuiying Huo; Di Jin 001; Yawen Li 001; Dongxiao He; Yu-Bin Yang; Lingfei Wu 001 (AAAI, 2023)

Graph Reciprocal Neural Networks by Abstracting Node as Attribute. - Liang Yang 002; Jiayi Wang; Dongxiao He; Chuan Wang 002; Xiaochun Cao; Bingxin Niu; Zhen Wang 004 (ICDM, 2023)

Contrastive Learning Meets Homophily: Two Birds with One Stone. - Dongxiao He; Jitao Zhao; Rui Guo; Zhiyong Feng 002; Di Jin 001; Yuxiao Huang; Zhen Wang 004; Weixiong Zhang (ICML, 2023)

A Generalized Deep Markov Random Fields Framework for Fake News Detection. - Yiqi Dong; Dongxiao He; Xiaobao Wang; Yawen Li 001; Xiaowen Su; Di Jin 001 (IJCAI, 2023)

Local-Global Fusion Augmented Graph Contrastive Learning Based on Generative Models. - Di Jin 001; Zhiqiang Wang; Cuiying Huo; Zhizhi Yu; Dongxiao He; Yuxiao Huang (KSEM (4), 2023)

Long Short-Term Graph Memory Against Class-imbalanced Over-smoothing. - Liang Yang 002; Jiayi Wang; Tingting Zhang; Dongxiao He; Chuan Wang 002; Yuanfang Guo; Xiaochun Cao; Bingxin Niu; Zhen Wang 004 (ACM Multimedia, 2023)

Propagation is All You Need: A New Framework for Representation Learning and Classifier Training on Graphs. - Jiaming Zhuo; Can Cui 005; Kun Fu; Bingxin Niu; Dongxiao He; Yuanfang Guo; Zhen Wang 004; Chuan Wang 002; Xiaochun Cao; Liang Yang 002 (ACM Multimedia, 2023)

Graph Neural Networks without Propagation. - Liang Yang 002; Qiuliang Zhang; Runjie Shi; Wenmiao Zhou; Bingxin Niu; Chuan Wang 002; Xiaochun Cao; Dongxiao He; Zhen Wang 004; Yuanfang Guo (WWW, 2023)

Amer: A New Attribute-Missing Network Embedding Approach. - Di Jin 001; Rui Wang 102; Tao Wang 074; Dongxiao He; Weiping Ding 001; Yuxiao Huang; Longbiao Wang; Witold Pedrycz (IEEE Trans. Cybern., 2023)

Adversarial Representation Mechanism Learning for Network Embedding. - Dongxiao He; Tao Wang 074; Lu Zhai; Di Jin 001; Liang Yang 002; Yuxiao Huang; Zhiyong Feng 002; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2023)

A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning. - Di Jin 001; Zhizhi Yu; Pengfei Jiao; Shirui Pan; Dongxiao He; Jia Wu 001; Philip S. Yu; Weixiong Zhang (IEEE Trans. Knowl. Data Eng., 2023)

Embedding text-rich graph neural networks with sequence and topical semantic structures. - Zhizhi Yu; Di Jin 001; Ziyang Liu 004; Dongxiao He; Xiao Wang 017; Hanghang Tong; Jiawei Han 001 (Knowl. Inf. Syst., 2023)

GCN for HIN via Implicit Utilization of Attention and Meta-Paths. - Di Jin 001; Zhizhi Yu; Dongxiao He; Carl Yang 001; Philip S. Yu; Jiawei Han 001 (IEEE Trans. Knowl. Data Eng., 2023)

HB-DSBM: Modeling the Dynamic Complex Networks From Community Level to Node Level. - Pengfei Jiao; Tianpeng Li; Huaming Wu; Chang-Dong Wang 001; Dongxiao He; Wenjun Wang 002 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Generative Evolutionary Anomaly Detection in Dynamic Networks. - Pengfei Jiao; Tianpeng Li; Yingjie Xie; Yinghui Wang; Wenjun Wang 002; Dongxiao He; Huaming Wu (IEEE Trans. Knowl. Data Eng., 2023)

Unveiling Implicit Deceptive Patterns in Multi-Modal Fake News via Neuro-Symbolic Reasoning. - Yiqi Dong; Dongxiao He; Xiaobao Wang; Youzhu Jin; Meng Ge; Carl Yang 001; Di Jin 001 (AAAI, 2024)

Improving Distinguishability of Class for Graph Neural Networks. - Dongxiao He; Shuwei Liu; Meng Ge; Zhizhi Yu; Guangquan Xu; Zhiyong Feng 002 (AAAI, 2024)

A New Mechanism for Eliminating Implicit Conflict in Graph Contrastive Learning. - Dongxiao He; Jitao Zhao; Cuiying Huo; Yongqi Huang; Yuxiao Huang; Zhiyong Feng 002 (AAAI, 2024)

GOODAT: Towards Test-Time Graph Out-of-Distribution Detection. - Luzhi Wang; Dongxiao He; He Zhang 012; Yixin Liu 001; Wenjie Wang; Shirui Pan; Di Jin 001; Tat-Seng Chua (AAAI, 2024)

Beyond the Known: Novel Class Discovery for Open-World Graph Learning. - Yucheng Jin; Yun Xiong; Juncheng Fang; Xixi Wu; Dongxiao He; Xing Jia; Bingchen Zhao; Philip S. Yu (DASFAA (6), 2024)

Multi-Modal Sarcasm Detection Based on Dual Generative Processes. - Huiying Ma; Dongxiao He; Xiaobao Wang; Di Jin 001; Meng Ge; Longbiao Wang (IJCAI, 2024)

Joint Domain Adaptive Graph Convolutional Network. - Niya Yang; Ye Wang; Zhizhi Yu; Dongxiao He; Xin Huang 001; Di Jin 001 (IJCAI, 2024)

LG-GNN: Local-Global Adaptive Graph Neural Network for Modeling Both Homophily and Heterophily. - Zhizhi Yu; Bin Feng; Dongxiao He; Zizhen Wang; Yuxiao Huang; Zhiyong Feng 002 (IJCAI, 2024)

Generalized Taxonomy-Guided Graph Neural Networks. - Yu Zhou 050; Di Jin 001; Jianguo Wei; Dongxiao He; Zhizhi Yu; Weixiong Zhang (IJCAI, 2024)

TUT4CRS: Time-aware User-preference Tracking for Conversational Recommendation System. - Dongxiao He; Jinghan Zhang 010; Xiaobao Wang; Meng Ge; Zhiyong Feng 002; Longbiao Wang; Xiaoke Ma 001 (ACM Multimedia, 2024)

Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering. - Dongxiao He; Lianze Shan; Jitao Zhao; Hengrui Zhang; Zhen Wang 004; Weixiong Zhang (NeurIPS, 2024)

FUG: Feature-Universal Graph Contrastive Pre-training for Graphs with Diverse Node Features. - Jitao Zhao; Di Jin 001; Meng Ge; Lianze Shan; Xin Wang 030; Dongxiao He; Zhiyong Feng 002 (NeurIPS, 2024)

Unified Graph Augmentations for Generalized Contrastive Learning on Graphs. - Jiaming Zhuo; Yintong Lu; Hui Ning; Kun Fu; Bingxin Niu; Dongxiao He; Chuan Wang 002; Yuanfang Guo; Zhen Wang 004; Xiaochun Cao; Liang Yang 002 (NeurIPS, 2024)

GAUSS: GrAph-customized Universal Self-Supervised Learning. - Liang Yang 002; Weixiao Hu; Jizhong Xu; Runjie Shi; Dongxiao He; Chuan Wang 002; Xiaochun Cao; Zhen Wang 004; Bingxin Niu; Yuanfang Guo (WWW, 2024)

Graph Contrastive Learning Reimagined: Exploring Universality. - Jiaming Zhuo; Can Cui 005; Kun Fu; Bingxin Niu; Dongxiao He; Chuan Wang 002; Yuanfang Guo; Zhen Wang 004; Xiaochun Cao; Liang Yang 002 (WWW, 2024)

AIMDiT: Modality Augmentation and Interaction via Multimodal Dimension Transformation for Emotion Recognition in Conversations. - Sheng Wu; Jiaxing Liu; Longbiao Wang; Dongxiao He; Xiaobao Wang; Jianwu Dang 001 (CoRR, 2024)

GA-GGD: Improving semantic discriminability in graph contrastive learning via Generative Adversarial Network. - Jitao Zhao; Dongxiao He; Meng Ge; Yongqi Huang; Lianze Shan; Yongbin Qin; Zhiyong Feng 002 (Inf. Fusion, 2024)

Spatio-temporal graph cross-correlation auto-encoding network for wind power prediction. - Ruiguo Yu; Yingzhou Sun; Dongxiao He; Jie Gao 008; Zhiqiang Liu 002; Mei Yu 004 (Int. J. Mach. Learn. Cybern., 2024)

Analyzing Heterogeneous Networks With Missing Attributes by Unsupervised Contrastive Learning. - Dongxiao He; Chundong Liang; Cuiying Huo; Zhiyong Feng 002; Di Jin 001; Liang Yang 002; Weixiong Zhang (IEEE Trans. Neural Networks Learn. Syst., 2024)

Text-Rich Graph Neural Networks With Subjective-Objective Semantic Modeling. - Yawen Li 001; Zhizhi Yu; Dongxiao He (IEEE Trans. Knowl. Data Eng., 2024)

TrustGNN: Graph Neural Network-Based Trust Evaluation via Learnable Propagative and Composable Nature. - Cuiying Huo; Dongxiao He; Chundong Liang; Di Jin 001; Tie Qiu 001; Lingfei Wu 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Reliable Data Augmented Contrastive Learning for Sequential Recommendation. - Mankun Zhao; Aitong Sun; Jian Yu 003; Xuewei Li 001; Dongxiao He; Ruiguo Yu; Mei Yu 004 (IEEE Trans. Big Data, 2024)

Backdoor Attack on Propagation-based Rumor Detectors. - Di Jin 001; Yujun Zhang; Bingdao Feng; Xiaobao Wang; Dongxiao He; Zhen Wang 004 (AAAI, 2025)

Towards Global-Topology Relation Graph for Inductive Knowledge Graph Completion. - Ling Ding 001; Lei Huang; Zhizhi Yu; Di Jin 001; Dongxiao He (AAAI, 2025)

Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling. - Yongqi Huang; Jitao Zhao; Dongxiao He; Di Jin 001; Yuxiao Huang; Zhen Wang 004 (AAAI, 2025)

Feature-Structure Adaptive Completion Graph Neural Network for Cold-start Recommendation. - Songyuan Lei; Xinglong Chang; Zhizhi Yu; Dongxiao He; Cuiying Huo; Jianrong Wang; Di Jin 001 (AAAI, 2025)

Contrastive Representation for Interactive Recommendation. - Jingyu Li; Zhiyong Feng 002; Dongxiao He; Hongqi Chen; Qinghang Gao; Guoli Wu (AAAI, 2025)

Integrating Co-Training with Edge Discrimination to Enhance Graph Neural Networks Under Heterophily. - Siqi Liu; Dongxiao He; Zhizhi Yu; Di Jin 001; Zhiyong Feng 002; Weixiong Zhang (AAAI, 2025)

Enriching Multimodal Sentiment Analysis Through Textual Emotional Descriptions of Visual-Audio Content. - Sheng Wu; Dongxiao He; Xiaobao Wang; Longbiao Wang; Jianwu Dang 001 (AAAI, 2025)

HeterGP: Bridging Heterogeneity in Graph Neural Networks with Multi-View Prompting. - Fengyu Yan; Xiaobao Wang; Dongxiao He; Longbiao Wang; Jianwu Dang 001; Di Jin 001 (AAAI, 2025)

Dynamic Neighborhood Modeling via Node-Subgraph Contrastive Learning for Graph-Based Fraud Detection. - Zhizhi Yu; Chundong Liang; Xinglong Chang; Dongxiao He; Di Jin 001; Jianguo Wei (AAAI, 2025)

LLGformer: Learnable Long-range Graph Transformer for Traffic Flow Prediction. - Di Jin 001; Cuiying Huo; Jiayi Shi; Dongxiao He; Jianguo Wei; Philip S. Yu (WWW, 2025)

Str-GCL: Structural Commonsense Driven Graph Contrastive Learning. - Dongxiao He; Yongqi Huang; Jitao Zhao; Xiaobao Wang; Zhen Wang 004 (WWW, 2025)

Beyond Homophily: Neighborhood Distribution-guided Graph Convolutional Networks. - Siqi Liu; Dongxiao He; Zhizhi Yu; Di Jin 001; Zhiyong Feng 002 (Expert Syst. Appl., 2025)

Graph contrastive learning with multiple information fusion. - Xiaobao Wang; Jun Yang; Zhiqiang Wang; Dongxiao He; Jitao Zhao; Yuxiao Huang; Di Jin 001 (Expert Syst. Appl., 2025)

Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning. - Cuiying Huo; Dongxiao He; Yawen Li 001; Di Jin 001; Jianwu Dang 001; Witold Pedrycz; Lingfei Wu 001; Weixiong Zhang (ACM Trans. Intell. Syst. Technol., 2025)

Dual Enhanced Meta-Learning With Adaptive Task Scheduler for Cold-Start Recommendation. - Dongxiao He; Jiaqi Cui; Xiaobao Wang; Guojie Song; Yuxiao Huang; Lingfei Wu 001 (IEEE Trans. Knowl. Data Eng., 2025)

A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities. - Pengfei Jiao; Hongjiang Chen; Xuan Guo; Zhidong Zhao; Dongxiao He; Di Jin 001 (CoRR, 2025)

Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective. - Di Jin 001; Jingyi Cao; Xiaobao Wang; Bingdao Feng; Dongxiao He; Longbiao Wang; Jianwu Dang 001 (CoRR, 2025)

KG-BiLM: Knowledge Graph Embedding via Bidirectional Language Models. - Zirui Chen; Xin Wang 030; Zhao Li 009; Wenbin Guo; Dongxiao He (CoRR, 2025)

Single-Node Trigger Backdoor Attacks in Graph-Based Recommendation Systems. - Runze Li; Di Jin 001; Xiaobao Wang; Dongxiao He; Bingdao Feng; Zhen Wang 004 (CoRR, 2025)

Distill & Contrast: A New Graph Self-Supervised Method With Approximating Nature Data Relationships. - Dongxiao He; Jitao Zhao; Rui Guo; Zhiyong Feng 002; Cuiying Huo; Di Jin 001; Witold Pedrycz; Weixiong Zhang (IEEE Trans. Knowl. Data Eng., 2025)

Elevating Knowledge-Enhanced Entity and Relationship Understanding for Sarcasm Detection. - Xiaobao Wang; Yujing Wang; Dongxiao He; Zhe Yu; Yawen Li 001; Longbiao Wang; Jianwu Dang 001; Di Jin 001 (IEEE Trans. Knowl. Data Eng., 2025)