D2CS: Dynamic Duty Cycle Scheme in an Opportunistic Routing Sensor Network. - Bingxin Niu; Heng Qi; Keqiu Li; Xiulong Liu; Weilian Xue (ICCCN, 2015)

Maximizing the Utility Without the Knowledge of the Link Capacity in a Wireless Sensor Network. - Bingxin Niu; Keqiu Li; Kai Lin; Weilian Xue (Ad Hoc Sens. Wirel. Networks, 2016)

An Advanced Maximum Utility Spectrum Allocation Algorithm Based on Graph Coloring Theory. - Weilian Xue; Xiaoyu Liu; Bingxin Niu (Ad Hoc Sens. Wirel. Networks, 2017)

Dynamic scheming the duty cycle in the opportunistic routing sensor network. - Bingxin Niu; Heng Qi; Keqiu Li; Xiulong Liu; Weilian Xue (Concurr. Comput. Pract. Exp., 2017)

A CRAHNs routing protocol based on the hops, channel number and channel capacity. - Weilian Xue; Zhibo Yuan; Bingxin Niu (Comput. Syst. Sci. Eng., 2017)

Why Do Attributes Propagate in Graph Convolutional Neural Networks? - Liang Yang 002; Chuan Wang 002; Junhua Gu; Xiaochun Cao; Bingxin Niu (AAAI, 2021)

Heterogeneous Graph Information Bottleneck. - Liang Yang 002; Fan Wu; Zichen Zheng; Bingxin Niu; Junhua Gu; Chuan Wang 002; Xiaochun Cao; Yuanfang Guo (IJCAI, 2021)

Diverse Message Passing for Attribute with Heterophily. - Liang Yang 002; Mengzhe Li; Liyang Liu; Bingxin Niu; Chuan Wang 002; Xiaochun Cao; Yuanfang Guo (NeurIPS, 2021)

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)

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)

JSON-based control model for SQL and NoSQL data conversion in hybrid cloud database. - Lei Zhang; Ke Pang; Jiangtao Xu; Bingxin Niu (J. Cloud Comput., 2022)

A Cross-Domain Federated Learning Framework for Wireless Human Sensing. - Kaixuan Zhang; Xiulong Liu; Xin Xie 001; Jiuwu Zhang; Bingxin Niu; Keqiu Li (IEEE Netw., 2022)

Distributed Task Offloading Method Based on Federated Reinforcement Learning in Vehicular Networks with Incomplete Information. - Rui Cao; Zhengchang Song; Bingxin Niu; Junhua Gu; Chunjie Li (ICA3PP (4), 2023)

A Hybrid Active and Passive Cache Method Based on Deep Learning in Edge Computing. - Zhengchang Song; Rui Cao; Bingxin Niu; Junhua Gu; Chunjie Li (ICA3PP (4), 2023)

Period Extraction for Traffic Flow Prediction. - Qingyuan Wang; Chen Chen; Long Zhang; Xiaoxuan Song; Honggang Li; Qingjie Zhao; Bingxin Niu; Junhua Gu (ICA3PP (3), 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)

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)

Self-supervised Graph Neural Networks via Low-Rank Decomposition. - Liang Yang 002; Runjie Shi; Qiuliang Zhang; Bingxin Niu; Zhen Wang 004; Xiaochun Cao; Chuan Wang 002 (NeurIPS, 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)

Improving Graph Contrastive Learning via Adaptive Positive Sampling. - Jiaming Zhuo; Feiyang Qin; Can Cui 005; Kun Fu; Bingxin Niu; Mengzhu Wang; Yuanfang Guo; Chuan Wang 002; Zhen Wang 004; Xiaochun Cao; Liang Yang 002 (CVPR, 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)

MAT-IGA: A Deadline and Priority-Aware Task Offloading Method in Resource-Constrained Vehicular Networks. - Long Zhang; Rui Cao; Wei Lei; Yazhou Wang; Zhenlong Xie; Bingxin Niu (IEEE Access, 2024)