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2020 – today
- 2024
[j25]Yang Li, Dongrui Wu, Suhang Wang
:
Future-generation attack and defense in neural networks. Future Gener. Comput. Syst. 152: 224 (2024)- [j24]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Imbalanced Node Classification With Synthetic Over-Sampling. IEEE Trans. Knowl. Data Eng. 36(12): 8515-8528 (2024) - [c123]Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang:
Spectral-Based Graph Neural Networks for Complementary Item Recommendation. AAAI 2024: 8868-8876 - [c122]Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han:
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs. ACL (Findings) 2024: 163-184 - [c121]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CIKM 2024: 2326-2335 - [c120]Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Shape-aware Graph Spectral Learning. CIKM 2024: 2692-2701 - [c119]Zhichao Hou, Minhua Lin, MohamadAli Torkamani, Suhang Wang, Xiaorui Liu:
Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier. DSAA 2024: 1-2 - [c118]Xianren Zhang, Dongwon Lee, Suhang Wang:
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector. ECCV (81) 2024: 196-213 - [c117]Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen:
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. EMNLP (Findings) 2024: 3675-3688 - [c116]Haoyu Wang, Ruirui Li, Zhengyang Wang, Xianfeng Tang, Danqing Zhang, Monica Xiao Cheng, Bing Yin, Jasha Droppo, Suhang Wang, Jing Gao:
LightLT: A Lightweight Representation Quantization Framework for Long-Tail Data. ICDE 2024: 1380-1393 - [c115]Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang:
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. ICLR 2024 - [c114]Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang:
Language Models as Semantic Indexers. ICML 2024 - [c113]Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar:
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. ICML 2024 - [c112]Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang:
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. KDD 2024: 4386-4397 - [c111]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD 2024: 4479-4489 - [c110]Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma:
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. KDD 2024: 5602-5612 - [c109]Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang:
Universal Prompt Optimizer for Safe Text-to-Image Generation. NAACL-HLT 2024: 6340-6354 - [c108]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. SDM 2024: 262-270 - [c107]Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen:
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. VLDB Workshops 2024 - [c106]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. WSDM 2024: 712-720 - [c105]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Interpretable Imitation Learning with Dynamic Causal Relations. WSDM 2024: 967-975 - [c104]Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang:
Hierarchical Query Classification in E-commerce Search. WWW (Companion Volume) 2024: 338-345 - [c103]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. WWW 2024: 914-923 - [i96]Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang:
Spectral-based Graph Neural Networks for Complementary Item Recommendation. CoRR abs/2401.02130 (2024) - [i95]Teng Xiao, Suhang Wang:
Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback. CoRR abs/2401.08959 (2024) - [i94]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. CoRR abs/2401.10394 (2024) - [i93]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. CoRR abs/2402.02321 (2024) - [i92]Enyan Dai, Minhua Lin, Suhang Wang:
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection. CoRR abs/2402.04435 (2024) - [i91]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. CoRR abs/2402.08824 (2024) - [i90]Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang:
Universal Prompt Optimizer for Safe Text-to-Image Generation. CoRR abs/2402.10882 (2024) - [i89]Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen:
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. CoRR abs/2402.11441 (2024) - [i88]Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma:
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. CoRR abs/2402.15680 (2024) - [i87]Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma:
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. CoRR abs/2403.06017 (2024) - [i86]Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang:
Hierarchical Query Classification in E-commerce Search. CoRR abs/2403.06021 (2024) - [i85]Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang:
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. CoRR abs/2403.10667 (2024) - [i84]Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Suhang Wang, Yu Meng, Jiawei Han:
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs. CoRR abs/2404.07103 (2024) - [i83]Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang:
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. CoRR abs/2405.10757 (2024) - [i82]Junjie Xu, Zongyu Wu, Minhua Lin, Xiang Zhang, Suhang Wang:
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning. CoRR abs/2406.01032 (2024) - [i81]Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang:
Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks. CoRR abs/2406.09836 (2024) - [i80]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR abs/2406.10425 (2024) - [i79]Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang:
Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. CoRR abs/2407.13989 (2024) - [i78]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CoRR abs/2407.17787 (2024) - [i77]Xianren Zhang, Dongwon Lee, Suhang Wang:
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector. CoRR abs/2407.19308 (2024) - [i76]Saptarshi Sengupta, Wenpeng Yin, Preslav Nakov, Shreya Ghosh, Suhang Wang:
Exploring Language Model Generalization in Low-Resource Extractive QA. CoRR abs/2409.18446 (2024) - [i75]Haitong Luo, Xuying Meng, Suhang Wang, Tianxiang Zhao, Fali Wang, Hanyun Cao, Yujun Zhang:
Enhance Graph Alignment for Large Language Models. CoRR abs/2410.11370 (2024) - [i74]Xianren Zhang, Xianfeng Tang, Hui Liu, Zongyu Wu, Qi He, Dongwon Lee, Suhang Wang:
Divide-Verify-Refine: Aligning LLM Responses with Complex Instructions. CoRR abs/2410.12207 (2024) - [i73]Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang, Xiang Zhang, Suhang Wang:
Trojan Prompt Attacks on Graph Neural Networks. CoRR abs/2410.13974 (2024) - [i72]Zhiwei Zhang, Fali Wang, Xiaomin Li, Zongyu Wu, Xianfeng Tang, Hui Liu, Qi He, Wenpeng Yin, Suhang Wang:
Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge. CoRR abs/2410.16454 (2024) - [i71]Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Chen:
Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation. CoRR abs/2410.17462 (2024) - 2023
- [j23]Huaisheng Zhu, Enyan Dai, Hui Liu, Suhang Wang:
Learning fair models without sensitive attributes: A generative approach. Neurocomputing 561: 126841 (2023) - [j22]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. 14(5): 92:1-92:23 (2023) - [j21]Enyan Dai, Suhang Wang:
Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information. IEEE Trans. Knowl. Data Eng. 35(7): 7103-7117 (2023) - [c102]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Towards Fair Graph Neural Networks via Graph Counterfactual. CIKM 2023: 669-678 - [c101]Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. ICDE 2023: 654-667 - [c100]Yitang Wang, Suhang Wang, Yong Pang, Xueguan Song:
Outlier Detection and Correction for Time Series Data of Tunnel Boring Machine. ICIRA (6) 2023: 254-261 - [c99]Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang:
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. KDD 2023: 368-379 - [c98]Teng Xiao, Zhengyu Chen, Suhang Wang:
Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. KDD 2023: 2764-2775 - [c97]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. KDD 2023: 3513-3524 - [c96]Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Xiao Cheng, Bing Yin, Suhang Wang, Philip S. Yu:
Exploiting Intent Evolution in E-commercial Query Recommendation. KDD 2023: 5162-5173 - [c95]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS 2023 - [c94]Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang:
Certifiably Robust Graph Contrastive Learning. NeurIPS 2023 - [c93]Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang:
Simple and Asymmetric Graph Contrastive Learning without Augmentations. NeurIPS 2023 - [c92]Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang:
You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. PAKDD (2) 2023: 40-52 - [c91]Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang:
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. RecSys 2023: 602-612 - [c90]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM 2023: 634-642 - [c89]Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang:
Unnoticeable Backdoor Attacks on Graph Neural Networks. WWW 2023: 2263-2273 - [i70]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR abs/2301.02791 (2023) - [i69]Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang:
Unnoticeable Backdoor Attacks on Graph Neural Networks. CoRR abs/2303.01263 (2023) - [i68]Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang:
Counterfactual Learning on Graphs: A Survey. CoRR abs/2304.01391 (2023) - [i67]Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang:
Self-Explainable Graph Neural Networks for Link Prediction. CoRR abs/2305.12578 (2023) - [i66]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. CoRR abs/2306.07919 (2023) - [i65]Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang:
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. CoRR abs/2306.08604 (2023) - [i64]Huaisheng Zhu, Guoji Fu, Zhimeng Guo, Zhiwei Zhang, Teng Xiao, Suhang Wang:
Fairness-aware Message Passing for Graph Neural Networks. CoRR abs/2306.11132 (2023) - [i63]Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang:
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. CoRR abs/2306.12232 (2023) - [i62]Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria:
Recent Developments in Recommender Systems: A Survey. CoRR abs/2306.12680 (2023) - [i61]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective. CoRR abs/2307.04937 (2023) - [i60]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR abs/2307.09688 (2023) - [i59]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Dynamic DAG Discovery for Interpretable Imitation Learning. CoRR abs/2310.00489 (2023) - [i58]Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang:
Learning How to Propagate Messages in Graph Neural Networks. CoRR abs/2310.00697 (2023) - [i57]Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang:
Certifiably Robust Graph Contrastive Learning. CoRR abs/2310.03312 (2023) - [i56]Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang:
Language Models As Semantic Indexers. CoRR abs/2310.07815 (2023) - [i55]Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Learning Graph Filters for Spectral GNNs via Newton Interpolation. CoRR abs/2310.10064 (2023) - [i54]Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang:
Simple and Asymmetric Graph Contrastive Learning without Augmentations. CoRR abs/2310.18884 (2023) - 2022
- [j20]Wen Zhang, B. Blair Braden, Gustavo Miranda, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang:
Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning. Neuroinformatics 20(2): 301-316 (2022) - [c88]Teng Xiao, Suhang Wang:
Towards Off-Policy Learning for Ranking Policies with Logged Feedback. AAAI 2022: 8700-8707 - [c87]Teng Xiao, Zhengyu Chen, Suhang Wang:
Representation Matters When Learning From Biased Feedback in Recommendation. CIKM 2022: 2220-2229 - [c86]Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang:
HP-GMN: Graph Memory Networks for Heterophilous Graphs. ICDM 2022: 1263-1268 - [c85]Enyan Dai, Shijie Zhou, Zhimeng Guo, Suhang Wang:
Label-Wise Graph Convolutional Network for Heterophilic Graphs. LoG 2022: 26 - [c84]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG 2022: 37 - [c83]Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang:
Decoupled Self-supervised Learning for Graphs. NeurIPS 2022 - [c82]Enyan Dai, Wei Jin, Hui Liu, Suhang Wang:
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. WSDM 2022: 181-191 - [c81]Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah:
Friend Story Ranking with Edge-Contextual Local Graph Convolutions. WSDM 2022: 1007-1015 - [c80]Teng Xiao, Suhang Wang:
Towards Unbiased and Robust Causal Ranking for Recommender Systems. WSDM 2022: 1158-1167 - [c79]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM 2022: 1433-1442 - [c78]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. WWW 2022: 1028-1036 - [i53]Enyan Dai, Wei Jin, Hui Liu, Suhang Wang:
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. CoRR abs/2201.00232 (2022) - [i52]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. CoRR abs/2202.11245 (2022) - [i51]Huaisheng Zhu, Suhang Wang:
Learning Fair Models without Sensitive Attributes: A Generative Approach. CoRR abs/2203.16413 (2022) - [i50]Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR abs/2204.08570 (2022) - [i49]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
On Consistency in Graph Neural Network Interpretation. CoRR abs/2205.13733 (2022) - [i48]Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang:
Decoupled Self-supervised Learning for Non-Homophilous Graphs. CoRR abs/2206.03601 (2022) - [i47]Teng Xiao, Zhengyu Chen, Suhang Wang:
Towards Bridging Algorithm and Theory for Unbiased Recommendation. CoRR abs/2206.03851 (2022) - [i46]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR abs/2206.05335 (2022) - [i45]Shijie Zhou, Zhimeng Guo, Charu C. Aggarwal, Xiang Zhang, Suhang Wang:
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning. CoRR abs/2208.01820 (2022) - [i44]Enyan Dai, Suhang Wang:
Towards Prototype-Based Self-Explainable Graph Neural Network. CoRR abs/2210.01974 (2022) - [i43]Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang:
HP-GMN: Graph Memory Networks for Heterophilous Graphs. CoRR abs/2210.08195 (2022) - [i42]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR abs/2212.08689 (2022) - 2021
- [j19]Xuying Meng, Suhang Wang, Zhimin Liang, Di Yao, Jihua Zhou, Yujun Zhang:
Semi-supervised anomaly detection in dynamic communication networks. Inf. Sci. 571: 527-542 (2021) - [j18]Yang Li, Wei Zhao, Erik Cambria, Suhang Wang, Steffen Eger:
Graph routing between capsules. Neural Networks 143: 345-354 (2021) - [j17]Xuying Meng, Yequan Wang, Suhang Wang, Di Yao, Yujun Zhang:
Interactive Anomaly Detection in Dynamic Communication Networks. IEEE/ACM Trans. Netw. 29(6): 2602-2615 (2021) - [c77]Porter Jenkins, Ahmad Farag, J. Stockton Jenkins, Huaxiu Yao, Suhang Wang, Zhenhui Li:
Neural Utility Functions. AAAI 2021: 7917-7925 - [c76]Enyan Dai, Suhang Wang:
Towards Self-Explainable Graph Neural Network. CIKM 2021: 302-311 - [c75]Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. KDD 2021: 218-226 - [c74]Enyan Dai, Charu Aggarwal, Suhang Wang:
NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. KDD 2021: 227-236 - [c73]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c72]