Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDChuan Shi
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j65]Qi Zhang
, Cheng Yang, Chuan Shi:
Adaptive negative representations for graph contrastive learning. AI Open 5: 79-86 (2024)- [j64]Chuan Shi, Junze Chen, Jiawei Liu, Cheng Yang:
Graph foundation model. Frontiers Comput. Sci. 18(6): 186355 (2024) - [j63]Ang Ma, Yanhua Yu, Chuan Shi, Zirui Guo, Tat-Seng Chua:
Cross-view hypergraph contrastive learning for attribute-aware recommendation. Inf. Process. Manag. 61(4): 103701 (2024) - [j62]Wenchuan Yang, Cheng Yang, Jichao Li, Yuejin Tan, Xin Lu, Chuan Shi:
Non-autoregressive personalized bundle generation. Inf. Process. Manag. 61(5): 103814 (2024) - [j61]Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang:
Generalizing Graph Neural Networks on Out-of-Distribution Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 46(1): 322-337 (2024) - [j60]Bo Yan, Cheng Yang, Chuan Shi, Yong Fang, Qi Li, Yanfang Ye, Junping Du:
Graph Mining for Cybersecurity: A Survey. ACM Trans. Knowl. Discov. Data 18(2): 47:1-47:52 (2024) - [j59]Chuan Shi, Houye Ji, Zhiyuan Lu, Ye Tang, Pan Li, Cheng Yang:
Distance Information Improves Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(3): 1030-1043 (2024) - [j58]Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang:
Debiased Graph Neural Networks With Agnostic Label Selection Bias. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4411-4422 (2024) - [j57]Chunchen Wang, Wei Wang, Cheng Yang, Chuan Shi, Ruobing Xie, Yuanfu Lu, Haili Yang, Xu Zhang:
Group-to-group recommendation with neural graph matching. World Wide Web (WWW) 27(2): 19 (2024) - [c197]Tianrui Jia, Haoyang Li, Cheng Yang, Tao Tao, Chuan Shi:
Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization. AAAI 2024: 8562-8570 - [c196]Yibo Li, Xiao Wang, Hongrui Liu, Chuan Shi:
A Generalized Neural Diffusion Framework on Graphs. AAAI 2024: 8707-8715 - [c195]Yanhu Mo, Xiao Wang, Shaohua Fan, Chuan Shi:
Graph Contrastive Invariant Learning from the Causal Perspective. AAAI 2024: 8904-8912 - [c194]Cheng Yang, Jixi Liu, Yunhe Yan, Chuan Shi:
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization. AAAI 2024: 9241-9249 - [c193]Feng Guo, Jiawei Liu, Jianwang Zhai, Jingyu Jia, Kang Zhao, Chuan Shi:
PGAU: Static IR Drop Analysis for Power Grid using Attention U-Net Architecture and Label Distribution Smoothing. ACM Great Lakes Symposium on VLSI 2024: 452-458 - [c192]Yang Liu, Deyu Bo, Chuan Shi:
Graph Distillation with Eigenbasis Matching. ICML 2024 - [c191]Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi:
Less is More: on the Over-Globalizing Problem in Graph Transformers. ICML 2024 - [c190]Fengqi Liang, Huan Zhao, Yuhan Quan, Wei Fang, Chuan Shi:
Customizing Graph Neural Network for CAD Assembly Recommendation. KDD 2024: 1746-1757 - [c189]Ruijia Wang, Haoran Dai, Cheng Yang, Le Song, Chuan Shi:
Advancing Molecule Invariant Representation via Privileged Substructure Identification. KDD 2024: 3188-3199 - [c188]Yuanxin Zhuang, Chuan Shi, Mengmei Zhang, Jinghui Chen, Lingjuan Lyu, Pan Zhou, Lichao Sun:
Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks? USENIX Security Symposium 2024 - [c187]Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi:
Graph Fairness Learning under Distribution Shifts. WWW 2024: 676-684 - [c186]Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, Jun Zhou:
Calibrating Graph Neural Networks from a Data-centric Perspective. WWW 2024: 745-755 - [c185]Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi:
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks. WWW 2024: 1003-1014 - [c184]Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi:
Endowing Pre-trained Graph Models with Provable Fairness. WWW 2024: 1045-1056 - [c183]Chuan Shi, Cheng Yang, Yuan Fang, Lichao Sun, Philip S. Yu:
Lecture-style Tutorial: Towards Graph Foundation Models. WWW (Companion Volume) 2024: 1264-1267 - [c182]Bo Yan, Yang Cao, Haoyu Wang, Wenchuan Yang, Junping Du, Chuan Shi:
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation. WWW 2024: 3919-3929 - [i68]Chenghua Gong, Yao Cheng, Xiang Li, Caihua Shan, Siqiang Luo, Chuan Shi:
Towards Learning from Graphs with Heterophily: Progress and Future. CoRR abs/2401.09769 (2024) - [i67]Yanhu Mo, Xiao Wang, Shaohua Fan, Chuan Shi:
Graph Contrastive Invariant Learning from the Causal Perspective. CoRR abs/2401.12564 (2024) - [i66]Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi:
Graph Fairness Learning under Distribution Shifts. CoRR abs/2401.16784 (2024) - [i65]Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi:
GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks. CoRR abs/2402.07197 (2024) - [i64]Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi:
Endowing Pre-trained Graph Models with Provable Fairness. CoRR abs/2402.12161 (2024) - [i63]Mengmei Zhang, Xiao Wang, Chuan Shi, Lingjuan Lyu, Tianchi Yang, Junping Du:
Minimum Topology Attacks for Graph Neural Networks. CoRR abs/2403.02723 (2024) - [i62]Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi:
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization. CoRR abs/2403.03599 (2024) - [i61]Sun Ao, Weilin Zhao, Xu Han, Cheng Yang, Zhiyuan Liu, Chuan Shi, Maosong Sun, Shengnan Wang, Teng Su:
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences. CoRR abs/2403.09347 (2024) - [i60]Cheng Yang, Jixi Liu, Yunhe Yan, Chuan Shi:
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization. CoRR abs/2403.12474 (2024) - [i59]Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi:
Less is More: on the Over-Globalizing Problem in Graph Transformers. CoRR abs/2405.01102 (2024) - [i58]Nian Liu, Shen Fan, Ting Bai, Peng Wang, Mingwei Sun, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Chuan Shi:
Learning Social Graph for Inactive User Recommendation. CoRR abs/2405.05288 (2024) - [i57]Ao Sun, Weilin Zhao, Xu Han, Cheng Yang, Zhiyuan Liu, Chuan Shi, Maosong Sun:
Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training. CoRR abs/2406.03488 (2024) - [i56]Yangbin Chen, Chenyang Xu, Chunfeng Liang, Yanbao Tao, Chuan Shi:
Speech-based Clinical Depression Screening: An Empirical Study. CoRR abs/2406.03510 (2024) - [i55]Wenchuan Yang, Cheng Yang, Jichao Li, Yuejin Tan, Xin Lu, Chuan Shi:
Non-autoregressive Personalized Bundle Generation. CoRR abs/2406.06925 (2024) - 2023
- [b4]Chuan Shi, Xiao Wang, Cheng Yang:
Advances in Graph Neural Networks. Synthesis Lectures on Data Mining and Knowledge Discovery, Springer 2023, ISBN 978-3-031-16173-5, pp. 1-198 - [j56]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) - [j55]Xiaojun Ma, Ziyao Li, Guojie Song, Chuan Shi:
Learning discrete adaptive receptive fields for graph convolutional networks. Sci. China Inf. Sci. 66(12) (2023) - [j54]Zheng-Yang Zhao, Jie Lin, Zhen Wang, Jianxin Guo, Xinke Zhan, Yu-An Huang, Chuan Shi, Wenzhun Huang:
SEBGLMA: Semantic Embedded Bipartite Graph Network for Predicting lncRNA-miRNA Associations. Int. J. Intell. Syst. 2023: 1-15 (2023) - [j53]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) - [j52]Weizhong Zhao, Wenjie Yao, Xingpeng Jiang, Tingting He, Chuan Shi, Xiaohua Hu:
An Explainable Framework for Predicting Drug-Side Effect Associations via Meta-Path-Based Feature Learning in Heterogeneous Information Network. IEEE ACM Trans. Comput. Biol. Bioinform. 20(6): 3635-3647 (2023) - [j51]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) - [j50]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) - [j49]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) - [j48]Nian Liu, Xiao Wang, Hui Han, Chuan Shi:
Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35(10): 10884-10896 (2023) - [j47]Meiqi Zhu, Xiao Wang, Chuan Shi, Yibo Li, Junping Du:
Towards Adaptive Information Fusion in Graph Convolutional Networks. IEEE Trans. Knowl. Data Eng. 35(12): 13055-13069 (2023) - [j46]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) - [j45]Yugang Ji, Chuan Shi, Yuan Fang:
Dynamic Meta-path Guided Temporal Heterogeneous Graph Neural Networks. World Sci. Annu. Rev. Artif. Intell. 1: 2350002:1-2350002:22 (2023) - [c181]Xumeng Gong, Cheng Yang, Chuan Shi:
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning. AAAI 2023: 4284-4292 - [c180]Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi:
Directed Acyclic Graph Structure Learning from Dynamic Graphs. AAAI 2023: 7512-7521 - [c179]Fengqi Liang, Huan Zhao, Zhenyi Wang, Wei Fang, Chuan Shi:
Retrieving GNN Architecture for Collaborative Filtering. CIKM 2023: 1379-1388 - [c178]Zhenyi Wang, Huan Zhao, Fengqi Liang, Chuan Shi:
Node-dependent Semantic Search over Heterogeneous Graph Neural Networks. CIKM 2023: 2646-2655 - [c177]Yijian Liu, Hongyi Zhang, Cheng Yang, Ao Li, Yugang Ji, Luhao Zhang, Tao Li, Jinyu Yang, Tianyu Zhao, Juan Yang, Hai Huang, Chuan Shi:
Datasets and Interfaces for Benchmarking Heterogeneous Graph Neural Networks. CIKM 2023: 5346-5350 - [c176]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 - [c175]Wenting Zhu, Zhe Liu, Zongyi Chen, Chuan Shi, Xi Zhang, Sanchuan Guo:
FedValidate: A Robust Federated Learning Framework Based on Client-Side Validation. DSC 2023: 337-344 - [c174]Ao Li, Yugang Ji, Guanyi Chu, Xiao Wang, Dong Li, Chuan Shi:
Clustering-Based Supervised Contrastive Learning for Identifying Risk Items on Heterogeneous Graph. ICASSP 2023: 1-5 - [c173]Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao:
Specformer: Spectral Graph Neural Networks Meet Transformers. ICLR 2023 - [c172]Yuxin Guo, Cheng Yang, Yuluo Chen, Jixi Liu, Chuan Shi, Junping Du:
A Data-centric Framework to Endow Graph Neural Networks with Out-Of-Distribution Detection Ability. KDD 2023: 638-648 - [c171]Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi:
Graph Contrastive Learning with Stable and Scalable Spectral Encoding. NeurIPS 2023 - [c170]Ruijia Wang, YiWu Sun, Yujie Luo, Shaochuan Li, Cheng Yang, Xingyi Cheng, Hui Li, Chuan Shi, Le Song:
Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization. NeurIPS 2023 - [c169]Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi:
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization. NeurIPS 2023 - [c168]Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi:
Provable Training for Graph Contrastive Learning. NeurIPS 2023 - [c167]Shuyun Gu, Xiao Wang, Chuan Shi:
Duplicate Multi-modal Entities Detection with Graph Contrastive Self-training Network. ECML/PKDD (2) 2023: 651-665 - [c166]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. SDM 2023: 712-720 - [c165]Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. SIGIR 2023: 2516-2520 - [c164]Yaoqi Liu, Cheng Yang, Tianyu Zhao, Hui Han, Siyuan Zhang, Jing Wu, Guangyu Zhou, Hai Huang, Hui Wang, Chuan Shi:
GammaGL: A Multi-Backend Library for Graph Neural Networks. SIGIR 2023: 2861-2870 - [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 - [i54]Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi:
A Survey on Spectral Graph Neural Networks. CoRR abs/2302.05631 (2023) - [i53]Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao:
Specformer: Spectral Graph Neural Networks Meet Transformers. CoRR abs/2303.01028 (2023) - [i52]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) - [i51]Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu:
A Post-Training Framework for Improving Heterogeneous Graph Neural Networks. CoRR abs/2304.00698 (2023) - [i50]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. CoRR abs/2304.01226 (2023) - [i49]Nian Liu, Xiao Wang, Hui Han, Chuan Shi:
Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network. CoRR abs/2304.12228 (2023) - [i48]Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi:
Provable Training for Graph Contrastive Learning. CoRR abs/2309.13944 (2023) - [i47]Cheng Yang, Deyu Bo, Jixi Liu, Yufei Peng, Boyu Chen, Haoran Dai, Ao Sun, Yue Yu, Yixin Xiao, Qi Zhang, Chunchen Wang, Yuxin Guo, Chuan Shi:
Data-centric Graph Learning: A Survey. CoRR abs/2310.04987 (2023) - [i46]Yang Liu, Deyu Bo, Chuan Shi:
Graph Condensation via Eigenbasis Matching. CoRR abs/2310.09202 (2023) - [i45]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Towards Graph Foundation Models: A Survey and Beyond. CoRR abs/2310.11829 (2023) - [i44]Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi:
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. CoRR abs/2311.13864 (2023) - [i43]Yibo Li, Xiao Wang, Hongrui Liu, Chuan Shi:
A Generalized Neural Diffusion Framework on Graphs. CoRR abs/2312.08616 (2023) - [i42]Tianrui Jia, Haoyang Li, Cheng Yang, Tao Tao, Chuan Shi:
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization. CoRR abs/2312.10988 (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]