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2020 – today
- 2023
[j50]Weizhong Zhao, Xueling Yuan, Xianjun Shen, Xingpeng Jiang, Chuan Shi, Tingting He, Xiaohua Hu:
Improving drug-drug interactions prediction with interpretability via meta-path-based information fusion. Briefings Bioinform. 24(2) (2023)- [j49]Xiao Wang
, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu:
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. IEEE Trans. Big Data 9(2): 415-436 (2023) - [j48]Aikun Xu, Ping Zhong, Yilin Kang, Jiongqiang Duan, Anning Wang, Mingming Lu, Chuan Shi:
THAN: Multimodal Transportation Recommendation With Heterogeneous Graph Attention Networks. IEEE Trans. Intell. Transp. Syst. 24(2): 1533-1543 (2023) - [j47]Houye Ji, Xiao Wang, Chuan Shi, Bai Wang, Philip S. Yu:
Heterogeneous Graph Propagation Network. IEEE Trans. Knowl. Data Eng. 35(1): 521-532 (2023) - [j46]Ruijia Wang, Chuan Shi, Tianyu Zhao, Xiao Wang, Yanfang Ye:
Heterogeneous Information Network Embedding With Adversarial Disentangler. IEEE Trans. Knowl. Data Eng. 35(2): 1581-1593 (2023) - [j45]Cheng Yang, Hao Wang, Jian Tang, Chuan Shi, Maosong Sun, Ganqu Cui, Zhiyuan Liu:
Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks. IEEE Trans. Neural Networks Learn. Syst. 34(5): 2271-2283 (2023) - [c164]Tianchi Yang, Haihan Gao, Cheng Yang, Chuan Shi, Qianlong Xie, Xingxing Wang, Dong Wang:
Memory-Enhanced Period-Aware Graph Neural Network for General POI Recommendation. DASFAA (2) 2023: 462-472 - [c163]Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin:
Learning to Distill Graph Neural Networks. WSDM 2023: 123-131 - [c162]Hao Wang, Yao Xu, Cheng Yang, Chuan Shi, Xin Li, Ning Guo, Zhiyuan Liu:
Knowledge-Adaptive Contrastive Learning for Recommendation. WSDM 2023: 535-543 - [c161]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. WWW 2023: 251-262 - [c160]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. WWW 2023: 630-640 - [i47]Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi:
A Survey on Spectral Graph Neural Networks. CoRR abs/2302.05631 (2023) - [i46]Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao:
Specformer: Spectral Graph Neural Networks Meet Transformers. CoRR abs/2303.01028 (2023) - [i45]Bo Yan, Cheng Yang, Chuan Shi, Yong Fang, Qi Li, Yanfang Ye, Junping Du:
Graph Mining for Cybersecurity: A Survey. CoRR abs/2304.00485 (2023) - [i44]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. CoRR abs/2304.00698 (2023) - [i43]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. CoRR abs/2304.01226 (2023) - [i42]Nian Liu, Xiao Wang, Hui Han, Chuan Shi:
Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network. CoRR abs/2304.12228 (2023) - 2022
- [b3]Chuan Shi, Xiao Wang, Philip S. Yu:
Heterogeneous Graph Representation Learning and Applications. Artificial Intelligence: Foundations, Theory, and Algorithms, Springer 2022, ISBN 978-981-16-6165-5, pp. 1-318 - [j44]Jiawei Liu, Chuan Shi, Cheng Yang, Zhiyuan Lu, Philip S. Yu:
A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources. AI Open 3: 40-57 (2022) - [j43]Tianchi Yang, Luhao Zhang, Cheng Yang, Chuan Shi, Maodi Hu, Tao Li, Dong Wang:
Hypergraph Clustering Network for Interaction Data. IEEE Data Eng. Bull. 45(4): 88-101 (2022) - [j42]Guanglin Niu, Bo Li, Yongfei Zhang, Yongpan Sheng, Chuan Shi, Jingyang Li, Shiliang Pu:
Joint semantics and data-driven path representation for knowledge graph reasoning. Neurocomputing 483: 249-261 (2022) - [j41]Jing Zhang, Qingyong Li, Yangli-ao Geng, Wen Wang, Wenju Sun, Chuan Shi, Zhengming Ding:
A zero-shot learning framework via cluster-prototype matching. Pattern Recognit. 124: 108469 (2022) - [j40]Yuyan Zheng, Chuan Shi, Xiaohuan Cao, Xiaoli Li, Bin Wu:
A Meta Path Based Method for Entity Set Expansion in Knowledge Graph. IEEE Trans. Big Data 8(3): 616-629 (2022) - [j39]Guojie Song, Chuan Shi, Yizhou Sun, Zhiyuan Liu:
Guest Editorial: Special Issue on Social Media Computing. IEEE Trans. Big Data 8(4): 953-954 (2022) - [j38]Yiding Zhang, Xiao Wang, Chuan Shi, Xunqiang Jiang, Yanfang Ye:
Hyperbolic Graph Attention Network. IEEE Trans. Big Data 8(6): 1690-1701 (2022) - [j37]Yiding Zhang, Xiao Wang, Nian Liu, Chuan Shi:
Embedding Heterogeneous Information Network in Hyperbolic Spaces. ACM Trans. Knowl. Discov. Data 16(2): 35:1-35:23 (2022) - [j36]Chuan Shi, Yuanfu Lu, Linmei Hu, Zhiyuan Liu, Huadong Ma:
RHINE: Relation Structure-Aware Heterogeneous Information Network Embedding. IEEE Trans. Knowl. Data Eng. 34(1): 433-447 (2022) - [j35]Xiao Wang, Yuanfu Lu, Chuan Shi, Ruijia Wang, Peng Cui, Shuai Mou:
Dynamic Heterogeneous Information Network Embedding With Meta-Path Based Proximity. IEEE Trans. Knowl. Data Eng. 34(3): 1117-1132 (2022) - [c159]Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou:
Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations. AAAI 2022: 3913-3921 - [c158]Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Robust Heterogeneous Graph Neural Networks against Adversarial Attacks. AAAI 2022: 4363-4370 - [c157]Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi:
OpenHGNN: An Open Source Toolkit for Heterogeneous Graph Neural Network. CIKM 2022: 3993-3997 - [c156]Tianchi Yang, Luhao Zhang, Chuan Shi, Cheng Yang, Siyong Xu, Ruiyu Fang, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang:
Gated Hypergraph Neural Network for Scene-Aware Recommendation. DASFAA (2) 2022: 199-215 - [c155]Luhao Zhang, Ruiyu Fang, Tianchi Yang, Maodi Hu, Tao Li, Chuan Shi, Dong Wang:
A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation. DASFAA (3) 2022: 351-363 - [c154]Yanru Hao, Tianchi Yang, Chuan Shi, Rui Wang, Ding Xiao:
An Effective Sentiment Analysis Model for Tobacco Consumption. ICCPR 2022: 496-502 - [c153]Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao:
Self-supervised Graph Neural Networks for Multi-behavior Recommendation. IJCAI 2022: 2052-2058 - [c152]Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun:
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. IJCAI 2022: 2441-2447 - [c151]Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang:
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure. NeurIPS 2022 - [c150]Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei:
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum. NeurIPS 2022 - [c149]Ruijia Wang, Xiao Wang, Chuan Shi, Le Song:
Uncovering the Structural Fairness in Graph Contrastive Learning. NeurIPS 2022 - [c148]Yiding Zhang, Chaozhuo Li, Xing Xie, Xiao Wang, Chuan Shi, Yuming Liu, Hao Sun, Liangjie Zhang, Weiwei Deng, Qi Zhang:
Geometric Disentangled Collaborative Filtering. SIGIR 2022: 80-90 - [c147]Tianchi Yang, Cheng Yang, Luhao Zhang, Chuan Shi, Maodi Hu, Huaijun Liu, Tao Li, Dong Wang:
Co-clustering Interactions via Attentive Hypergraph Neural Network. SIGIR 2022: 859-869 - [c146]Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi:
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. SIGIR 2022: 2776-2789 - [c145]Zhenyi Wang, Huan Zhao, Chuan Shi:
Profiling the Design Space for Graph Neural Networks based Collaborative Filtering. WSDM 2022: 1109-1119 - [c144]Cheng Yang, Chunchen Wang, Yuanfu Lu, Xumeng Gong, Chuan Shi, Wei Wang, Xu Zhang:
Few-shot Link Prediction in Dynamic Networks. WSDM 2022: 1245-1255 - [c143]Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. WWW 2022: 1248-1258 - [c142]Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao, Junping Du:
Prohibited Item Detection via Risk Graph Structure Learning. WWW 2022: 1434-1443 - [c141]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. WWW 2022: 1601-1610 - [i41]Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi:
Compact Graph Structure Learning via Mutual Information Compression. CoRR abs/2201.05540 (2022) - [i40]Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang:
Debiased Graph Neural Networks with Agnostic Label Selection Bias. CoRR abs/2201.07708 (2022) - [i39]Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou:
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. CoRR abs/2201.11349 (2022) - [i38]Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi:
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network. CoRR abs/2202.09177 (2022) - [i37]Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi:
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022. CoRR abs/2203.01820 (2022) - [i36]Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun:
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks. CoRR abs/2205.03811 (2022) - [i35]Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
KGNN: Distributed Framework for Graph Neural Knowledge Representation. CoRR abs/2205.08285 (2022) - [i34]Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang:
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure. CoRR abs/2209.14107 (2022) - [i33]Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei:
Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum. CoRR abs/2210.02330 (2022) - [i32]Ruijia Wang, Xiao Wang, Chuan Shi, Le Song:
Uncovering the Structural Fairness in Graph Contrastive Learning. CoRR abs/2210.03011 (2022) - [i31]Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi:
Directed Acyclic Graph Structure Learning from Dynamic Graphs. CoRR abs/2211.17029 (2022) - [i30]Yining Wang, Xumeng Gong, Shaochuan Li, Bing Yang, YiWu Sun, Chuan Shi, Yangang Wang, Cheng Yang, Hui Li, Le Song:
xTrimoABFold: De novo Antibody Structure Prediction without MSA. CoRR abs/2212.00735 (2022) - [i29]Xumeng Gong, Cheng Yang, Chuan Shi:
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning. CoRR abs/2212.07035 (2022) - 2021
- [b2]Cheng Yang, Zhiyuan Liu, Cunchao Tu, Chuan Shi, Maosong Sun:
Network Embedding: Theories, Methods, and Applications. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2021, pp. 1-242 - [j34]Chuan Shi, Jiayu Ding, Xiaohuan Cao, Linmei Hu, Bin Wu, Xiaoli Li:
Entity set expansion in knowledge graph: a heterogeneous information network perspective. Frontiers Comput. Sci. 15(1): 151307 (2021) - [j33]Linmei Hu, Mengmei Zhang, Shaohua Li, Jinghan Shi, Chuan Shi, Cheng Yang, Zhiyuan Liu:
Text-Graph Enhanced Knowledge Graph Representation Learning. Frontiers Artif. Intell. 4: 697856 (2021) - [j32]Yugang Ji, Mingyang Yin, Hongxia Yang, Jingren Zhou, Vincent W. Zheng, Chuan Shi, Yuan Fang:
Accelerating Large-Scale Heterogeneous Interaction Graph Embedding Learning via Importance Sampling. ACM Trans. Knowl. Discov. Data 15(1): 10:1-10:23 (2021) - [j31]Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu:
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 33(4): 1413-1425 (2021) - [j30]Tianchi Yang, Linmei Hu, Chuan Shi, Houye Ji, Xiaoli Li, Liqiang Nie:
HGAT: Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification. ACM Trans. Inf. Syst. 39(3): 32:1-32:29 (2021) - [c140]Houye Ji, Junxiong Zhu, Xiao Wang, Chuan Shi, Bai Wang, Xiaoye Tan, Yanghua Li, Shaojian He:
Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. AAAI 2021: 232-239 - [c139]Deyu Bo, Xiao Wang, Chuan Shi, Huawei Shen:
Beyond Low-frequency Information in Graph Convolutional Networks. AAAI 2021: 3950-3957 - [c138]Yi Li, Yilun Jin, Guojie Song, Zihao Zhu, Chuan Shi, Yiming Wang:
GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks. AAAI 2021: 4206-4214 - [c137]Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi:
Learning to Pre-train Graph Neural Networks. AAAI 2021: 4276-4284 - [c136]Jianan Zhao, Xiao Wang, Chuan Shi, Binbin Hu, Guojie Song, Yanfang Ye:
Heterogeneous Graph Structure Learning for Graph Neural Networks. AAAI 2021: 4697-4705 - [c135]Linmei Hu, Tianchi Yang, Luhao Zhang, Wanjun Zhong, Duyu Tang, Chuan Shi, Nan Duan, Ming Zhou:
Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge. ACL/IJCNLP (1) 2021: 754-763 - [c134]Xunqiang Jiang, Yuanfu Lu, Yuan Fang, Chuan Shi:
Contrastive Pre-Training of GNNs on Heterogeneous Graphs. CIKM 2021: 803-812 - [c133]Hao Wang, Cheng Yang, Chuan Shi:
Neural Information Diffusion Prediction with Topic-Aware Attention Network. CIKM 2021: 1899-1908 - [c132]Siyong Xu, Cheng Yang, Chuan Shi, Yuan Fang, Yuxin Guo, Tianchi Yang, Luhao Zhang, Maodi Hu:
Topic-aware Heterogeneous Graph Neural Network for Link Prediction. CIKM 2021: 2261-2270 - [c131]Yugang Ji, Chuan Shi, Xiao Wang:
Prohibited Item Detection on Heterogeneous Risk Graphs. CIKM 2021: 3867-3877 - [c130]Wenrui Wu, Tao Tao, Jing Shang, Ding Xiao, Chuan Shi, Yong Jiang:
Sequence Attention for Multivariate Time Series Forecasting. DSC 2021: 83-90 - [c129]Hsi-Wen Chen, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Chuan Shi, Philip S. Yu, Ming-Syan Chen:
Structure-Aware Parameter-Free Group Query via Heterogeneous Information Network Transformer. ICDE 2021: 2075-2080 - [c128]Houye Ji, Cheng Yang, Chuan Shi, Pan Li:
Heterogeneous Graph Neural Network with Distance Encoding. ICDM 2021: 1138-1143 - [c127]Guanyi Chu, Xiao Wang, Chuan Shi, Xunqiang Jiang:
CuCo: Graph Representation with Curriculum Contrastive Learning. IJCAI 2021: 2300-2306 - [c126]Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang:
Pre-training on Large-Scale Heterogeneous Graph. KDD 2021: 756-766 - [c125]Xiao Wang, Nian Liu, Hui Han, Chuan Shi:
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. KDD 2021: 1726-1736 - [c124]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c123]Chuan Shi, Yuan Fang, Yanfang Ye, Jiawei Zhang:
The 4th Workshop on Heterogeneous Information Network Analysis and Applications (HENA 2021). KDD 2021: 4157-4158 - [c122]Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang:
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration. NeurIPS 2021: 23768-23779 - [c121]Tianchi Yang, Linmei Hu, Luhao Zhang, Chuan Shi, Cheng Yang, Nan Duan, Ming Zhou:
Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction. PAKDD (3) 2021: 325-337 - [c120]Yuanxin Zhuang, Chuan Shi, Cheng Yang, Fuzhen Zhuang, Yangqiu Song:
Semantic-Specific Hierarchical Alignment Network for Heterogeneous Graph Adaptation. ECML/PKDD (2) 2021: 335-350 - [c119]Yugang Ji, Tianrui Jia, Yuan Fang, Chuan Shi:
Dynamic Heterogeneous Graph Embedding via Heterogeneous Hawkes Process. ECML/PKDD (1) 2021: 388-403 - [c118]Chen Li, Linmei Hu, Chuan Shi, Guojie Song, Yuanfu Lu:
Sequence-aware Heterogeneous Graph Neural Collaborative Filtering. SDM 2021: 64-72 - [c117]Chen Li, Yuanfu Lu, Wei Wang, Chuan Shi, Ruobing Xie, Haili Yang, Cheng Yang, Xu Zhang, Leyu Lin:
Package Recommendation with Intra- and Inter-Package Attention Networks. SIGIR 2021: 595-604 - [c116]Ruijia Wang, Shuai Mou, Xiao Wang, Wanpeng Xiao, Qi Ju, Chuan Shi, Xing Xie:
Graph Structure Estimation Neural Networks. WWW 2021: 342-353 - [c115]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. WWW 2021: 1215-1226 - [c114]Cheng Yang, Jiawei Liu, Chuan Shi:
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. WWW 2021: 1227-1237 - [c113]Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song:
Lorentzian Graph Convolutional Networks. WWW 2021: 1249-1261 - [c112]Houye Ji, Junxiong Zhu, Chuan Shi, Xiao Wang, Bai Wang, Chaoyu Zhang, Zixuan Zhu, Feng Zhang, Yanghua Li:
Large-scale Comb-K Recommendation. WWW 2021: 2512-2523 - [i28]Deyu Bo, Xiao Wang, Chuan Shi, Huawei Shen:
Beyond Low-frequency Information in Graph Convolutional Networks. CoRR abs/2101.00797 (2021) - [i27]Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui:
Interpreting and Unifying Graph Neural Networks with An Optimization Framework. CoRR abs/2101.11859 (2021) - [i26]Cheng Yang, Jiawei Liu, Chuan Shi:
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. CoRR abs/2103.02885 (2021) - [i25]Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song:
Lorentzian Graph Convolutional Networks. CoRR abs/2104.07477 (2021) - [i24]Xiao Wang, Nian Liu, Hui Han, Chuan Shi:
Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. CoRR abs/2105.09111 (2021) - [i23]Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang:
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration. CoRR abs/2109.14285 (2021) - [i22]Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang:
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs. CoRR abs/2111.10657 (2021) - 2020
- [j29]Linmei Hu, Chen Li, Chuan Shi, Cheng Yang, Chao Shao:
Graph neural news recommendation with long-term and short-term interest modeling. Inf. Process. Manag. 57(2): 102142 (2020) - [j28]Yugang Ji, Chuan Shi, Yuan Fang, Xiangnan Kong, Mingyang Yin:
Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks. Inf. Process. Manag. 57(6): 102338 (2020) - [j27]Linmei Hu, Jiayu Ding, Chuan Shi, Chao Shao, Shaohua Li:
Graph neural entity disambiguation. Knowl. Based Syst. 195: 105620 (2020) - [j26]Ding Xiao, Li Song, Ruijia Wang, Xiaotian Han, Yanan Cai, Chuan Shi:
Embedding geographic information for anomalous trajectory detection. World Wide Web 23(5): 2789-2809 (2020) - [c111]Yilun Jin, Guojie Song, Chuan Shi:
GraLSP: Graph Neural Networks with Local Structural Patterns. AAAI 2020: 4361-4368 - [c110]Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng:
FlowScope: Spotting Money Laundering Based on Graphs. AAAI 2020: 4731-4738 - [c109]Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li:
Multi-Component Graph Convolutional Collaborative Filtering. AAAI 2020: 6267-6274 - [c108]Linmei Hu, Siyong Xu, Chen Li, Cheng Yang, Chuan Shi, Nan Duan, Xing Xie, Ming Zhou:
Graph Neural News Recommendation with Unsupervised Preference Disentanglement. ACL 2020: 4255-4264 - [c107]Shuang Mo, Yifei Wang, Ding Xiao, Wenrui Wu, Shaohua Fan, Chuan Shi:
Encrypted Traffic Classification Using Graph Convolutional Networks. ADMA 2020: 207-219 - [c106]Mingjun Ma, Bo Peng, Ding Xiao, Yugang Ji, Chuan Shi:
STCNet: Spatial-Temporal Convolution Network for Traffic Speed Prediction. ADMA 2020: 315-323 - [c105]Jing Zhang, Yangli-ao Geng, Qingyong Li, Chuan Shi:
More Than One: A Cluster-Prototype Matching Framework for Zero-Shot Learning. CIKM 2020: 1803-1812 - [c104]