Real-Time Vehicle Route Guidance Based on Connected Vehicles. - Daxin Tian; Yong Yuan; Jianshan Zhou; Yunpeng Wang; Guangquan Lu; Haiying Xia (GreenCom/iThings/CPScom, 2013)

The resilience of interdependent transportation networks under targeted attack. - Peng Zhang; Baisong Cheng; Zhuang Zhao; Daqing Li; Guangquan Lu; Yunpeng Wang; Jinghua Xiao (CoRR, 2013)

Difference Factor' KNN Collaborative Filtering Recommendation Algorithm. - Wenzhong Liang; Guangquan Lu; Xiaoyu Ji; Jian Li; Dingrong Yuan (ADMA, 2014)

Travel time reliability affected by accident in freeway with connected vehicles. - Fangshu Lei; Yunpeng Wang; Guangquan Lu; Daxin Tian (ITSC, 2014)

A rear-end collision avoidance system of connected vehicles. - Liang Li; Guangquan Lu; Yunpeng Wang; Daxin Tian (ITSC, 2014)

A rule based control algorithm of connected vehicles in uncontrolled intersection. - Guangquan Lu; Lumiao Li; Yunpeng Wang; Ran Zhang; Zewen Bao; Haichong Chen (ITSC, 2014)

A Bayesian Compressive Sensing Vehicular Location Method Based on Three-Dimensional Radio Frequency. - Yunpeng Wang; Xuting Duan; Daxin Tian; Jianshan Zhou; Yingrong Lu; Guangquan Lu (Int. J. Distributed Sens. Networks, 2014)

Logit-Based Analysis of Drivers' Crossing Behavior at Unsignalized Intersections in China. - Guangquan Lu; Miaomiao Liu; Yunpeng Wang; Huasen Wan; Daxin Tian (Hum. Factors, 2015)

Analysis string stability of a new car-following model considering response time. - Junjie Zhang 003; Yunpeng Wang; Guangquan Lu; Wenmin Long (CASE, 2017)

The α-reliable path problem in stochastic road networks with link correlations: A moment-matching-based path finding algorithm. - Peng Chen 021; Rui Tong; Guangquan Lu; Yunpeng Wang (Expert Syst. Appl., 2018)

Unsupervised feature selection with graph learning via low-rank constraint. - Guangquan Lu; Bo Li 117; Weiwei Yang; Jian Yin 001 (Multim. Tools Appl., 2018)

An Adaptive Control Method for Arterial Signal Coordination Based on Deep Reinforcement Learning. - Peng Chen 021; Zemao Zhu; Guangquan Lu (ITSC, 2019)

A Nonlinear Clustering Algorithm via Kernel Function and Locality Structure Learning. - Linjun Chen; Guangquan Lu; Guoqiu Wen; Jiaye Li 001; Malong Tan (SSCI, 2019)

A Clustering Algorithm via Kernel Function and Locality Preserving Projections. - Mengmeng Zhan; Guangquan Lu; Guoqiu Wen; Leyuan Zhang; Lin Wu (SSCI, 2019)

A Speed Control Method at Successive Signalized Intersections Under Connected Vehicles Environment. - Yingrong Lu; Xiaotong Xu; Chuan Ding; Guangquan Lu (IEEE Intell. Transp. Syst. Mag., 2019)

Tunable and Transferable RBF Model for Short-Term Traffic Forecasting. - Pinlong Cai; Yunpeng Wang; Guangquan Lu (IEEE Trans. Intell. Transp. Syst., 2019)

Influence of Driving Behaviors on the Stability in Car Following. - Yunpeng Wang; Junjie Zhang 003; Guangquan Lu (IEEE Trans. Intell. Transp. Syst., 2019)

DGRL: Text Classification with Deep Graph Residual Learning. - Boyan Chen; Guangquan Lu; Bo Peng; Wenzhen Zhang (ADMA, 2020)

How Driving Experience Affect Trust in Automation from Level 3 Automated Vehicles? An Experimental Analysis. - Mengxia Jin; Guangquan Lu; Facheng Chen; Xi Shi (ITSC, 2020)

Multi-task learning using a hybrid representation for text classification. - Guangquan Lu; Jiangzhang Gan; Jian Yin 001; Zhiping Luo; Bo Li 117; Xishun Zhao (Neural Comput. Appl., 2020)

Local Structure Preservation for Nonlinear Clustering. - Linjun Chen; Guangquan Lu; Yangding Li; Jiaye Li 001; Malong Tan (Neural Process. Lett., 2020)

Using Locality Preserving Projections to Improve the Performance of Kernel Clustering. - Mengmeng Zhan; Guangquan Lu; Guoqiu Wen; Leyuan Zhang; Lin Wu (Neural Process. Lett., 2020)

Multi-task learning using variational auto-encoder for sentiment classification. - Guangquan Lu; Xishun Zhao; Jian Yin 001; Weiwei Yang; Bo Li 117 (Pattern Recognit. Lett., 2020)

Sparse Graph Connectivity for Image Segmentation. - Xiaofeng Zhu 001; Shichao Zhang 001; Jilian Zhang; Yonggang Li; Guangquan Lu; Yang Yang 002 (ACM Trans. Knowl. Discov. Data, 2020)

Spectral clustering via half-quadratic optimization. - Xiaofeng Zhu 001; Jiangzhang Gan; Guangquan Lu; Jiaye Li 001; Shichao Zhang 001 (World Wide Web, 2020)

Semi-supervised Feature Selection Based on Cost-Sensitive and Structural Information. - Yiling Tao; Guangquan Lu; Chaoqun Ma; Zidong Su; Zehui Hu (ADC, 2021)

Entity Relations Based Pointer-Generator Network for Abstractive Text Summarization. - Tiancheng Huang; Guangquan Lu; Zexin Li; Jiagang Song; Lijuan Wu (ADMA, 2021)

Balanced Spectral Clustering Algorithm Based on Feature Selection. - Qimin Luo; Guangquan Lu; Guoqiu Wen; Zidong Su; Xingyi Liu; Jian Wei (ADMA, 2021)

Temporal Attention-Based Graph Convolution Network for Taxi Demand Prediction in Functional Areas. - Yue Wang 052; Jianbo Li; Aite Zhao; Zhiqiang Lv; Guangquan Lu (WASA (1), 2021)

Learning Representation From Concurrence-Words Graph For Aspect Sentiment Classification. - Guangquan Lu; Jihong Huang (Comput. J., 2021)

Multi-View Gated Graph Convolutional Network for Aspect-Level Sentiment Classification. - Lijuan Wu; Guixian Zhang; Zhi Lei; Zhirong Huang; Guangquan Lu (ADMA (1), 2022)

One-Stage Deep Channels Attention Network for Remote Sensing Images Object Detection. - Jinyun Tang; Wenzhen Zhang; Guixian Zhang; Rongjiao Liang; Guangquan Lu (APWeb/WAIM (2), 2022)

Personalized Headline Generation with Enhanced User Interest Perception. - Kui Zhang; Guangquan Lu; Guixian Zhang; Zhi Lei; Lijuan Wu (ICANN (2), 2022)

Multi-View Graph Autoencoder for Unsupervised Graph Representation Learning. - Jingci Li; Guangquan Lu; Zhengtian Wu (ICPR, 2022)

Effect analysis of connected information on youth driver's performance in highway driving. - Junda Zhai; Guangquan Lu; Facheng Chen (ITSC, 2022)

A Self-supervised Graph Autoencoder with Barlow Twins. - Jingci Li; Guangquan Lu; Jiecheng Li (PRICAI (2), 2022)

Aspect sentiment analysis with heterogeneous graph neural networks. - Guangquan Lu; Jiecheng Li; Jian Wei (Inf. Process. Manag., 2022)

An approximation lagrangian-based algorithm for the maximum clique problem via deterministic annealing neural network. - Jinyu Dai; Zhengtian Wu; Hamid Reza Karimi; Baoping Jiang; Guangquan Lu (J. Frankl. Inst., 2022)

Graph convolutional networks of reconstructed graph structure with constrained Laplacian rank. - Mengmeng Zhan; Jiangzhang Gan; Guangquan Lu; Yingying Wan (Multim. Tools Appl., 2022)

Self-paced hybrid dilated convolutional neural networks. - Wenzhen Zhang; Guangquan Lu; Shichao Zhang 001; Yonggang Li (Multim. Tools Appl., 2022)

Semi-Supervised Classification of Graph Convolutional Networks with Laplacian Rank Constraints. - Haiqi Zhang; Guangquan Lu; Mengmeng Zhan; Beixian Zhang (Neural Process. Lett., 2022)

Risk Field Model of Driving and Its Application in Modeling Car-Following Behavior. - Haitian Tan; Guangquan Lu; Miaomiao Liu (IEEE Trans. Intell. Transp. Syst., 2022)

Effect of the Uncertainty Level of Vehicle-Position Information on the Stability and Safety of the Car-Following Process. - Junjie Zhang 003; Guangquan Lu; Haiyang Yu 002; Yunpeng Wang; Can Yang (IEEE Trans. Intell. Transp. Syst., 2022)

Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties. - Yadan Han; Guangquan Lu; Jiecheng Li; Fuqing Ling; Wanxi Chen; Liang Zhang (KSEM (1), 2023)

Multi-teacher Self-training for Semi-supervised Node Classification with Noisy Labels. - Yujing Liu; Zongqian Wu; Zhengyu Lu; Guoqiu Wen; Junbo Ma; Guangquan Lu; Xiaofeng Zhu 001 (ACM Multimedia, 2023)

Multi-view representation model based on graph autoencoder. - Jingci Li; Guangquan Lu; Zhengtian Wu; Fuqing Ling (Inf. Sci., 2023)

A Method of Identifying Personalized Car-Following Characteristics for Adaptive Cruise Control System. - Wenmin Long; Guangquan Lu (IEEE Trans. Intell. Transp. Syst., 2023)

Coupling Control of Traffic Signal and Entry Lane at Isolated Intersections Under the Mixed-Autonomy Traffic Environment. - Rongjian Dai; Chuan Ding; Xinkai Wu; Bin Yu; Guangquan Lu (IEEE Trans. Intell. Transp. Syst., 2023)

Modeling Vehicle Paths at Intersections: A Unified Approach Based on Entrance and Exit Lanes. - Guangquan Lu; Jun Hua; Haoyi Zhao; Miaomiao Liu; Jin Xu 008; Fang Zong (IEEE Trans. Intell. Transp. Syst., 2023)

GraphDHV: Graph Neural Network with Dual Hybrid View on Imbalanced Node Classification. - Longqing Du; Guangquan Lu; Yadan Han; Zhiping Luo; Guoqiu Wen; Liang Zhang; Wanxin Chen; Shichao Zhang 001 (COCOON (2), 2024)

Joint Graph Augmentation and Adaptive Synthetic Sampling for Imbalanced Node Classification. - Guangquan Lu; Wanxin Chen; Yadan Han; Jiamin Tang; Faliang Huang (NLPCC (4), 2024)

Data-driven Conditional Instrumental Variables for Debiasing Recommender Systems. - Zhirong Huang; Shichao Zhang 001; Debo Cheng; Jiuyong Li; Lin Liu 003; Guangquan Lu (CoRR, 2024)

GS-CBR-KBQA: Graph-structured case-based reasoning for knowledge base question answering. - Jiecheng Li; Xudong Luo; Guangquan Lu (Expert Syst. Appl., 2024)

Link prediction in multilayer networks using weighted reliable local random walk algorithm. - Zhiping Luo; Jian Yin 001; Guangquan Lu; Mohammad Reza Rahimi (Expert Syst. Appl., 2024)

A unified risk field-based driving behavior model for car-following and lane-changing behaviors simulation. - Haitian Tan; Guangquan Lu; Zhaojie Wang; Jun Hua; Miaomiao Liu (Simul. Model. Pract. Theory, 2024)

A Risk-Field Based Motion Planning Method for Multi-Vehicle Conflict Scenario. - Zhaojie Wang; Guangquan Lu; Haitian Tan; Miaomiao Liu (IEEE Trans. Veh. Technol., 2024)

Driving Behavior Model for Multi-Vehicle Interaction at Uncontrolled Intersections Based on Risk Field Considering Drivers' Visual Field Characteristics. - Zhaojie Wang; Guangquan Lu; Haitian Tan (IEEE Trans. Intell. Transp. Syst., 2024)

Hyper-Relational Knowledge Representation Learning with Multi-Hypergraph Disentanglement. - Jiecheng Li; Xudong Luo; Guangquan Lu; Shichao Zhang 001 (WWW, 2025)

Identifying local useful information for attribute graph anomaly detection. - Penghui Xi; Debo Cheng; Guangquan Lu; Zhenyun Deng; Guixian Zhang; Shichao Zhang 001 (Neurocomputing, 2025)

Efficient Adaptive Label Refinement for label noise learning. - Wenzhen Zhang; Debo Cheng; Guangquan Lu; Bo Zhou; Jiaye Li 001; Shichao Zhang 001 (Neurocomputing, 2025)

Graph similarity learning for cross-level interactions. - Cuifang Zou; Guangquan Lu; Longqing Du; Xuxia Zeng; Shilong Lin (Inf. Process. Manag., 2025)

DHRL4HKG: A Dual-Hypergraph Representation Learning for Hyper-Relational Knowledge Graphs. - Jiecheng Li; Xudong Luo; Guangquan Lu; Shichao Shang 001 (Knowl. Based Syst., 2025)