Enyan Dai

According to our database, Enyan Dai authored at least 27 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection.

Enyan Dai, Minhua Lin, Suhang Wang

CoRR, 2024

2023

Learning fair models without sensitive attributes: A generative approach.

Huaisheng Zhu, Enyan Dai, Hui Liu, Suhang Wang

Neurocomputing, December, 2023

Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information.

Enyan Dai, Suhang Wang

IEEE Trans. Knowl. Data Eng., July, 2023

Learning Graph Filters for Spectral GNNs via Newton Interpolation.

Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang

CoRR, 2023

Unnoticeable Backdoor Attacks on Graph Neural Networks.

Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang

Proceedings of the ACM Web Conference 2023, 2023

Certifiably Robust Graph Contrastive Learning.

Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy.

Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Towards Prototype-Based Self-Explainable Graph Neural Network.

Enyan Dai, Suhang Wang

CoRR, 2022

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability.

Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang

CoRR, 2022

Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features.

Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels.

Enyan Dai, Wei Jin, Hui Liu, Suhang Wang

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Label-Wise Graph Convolutional Network for Heterophilic Graphs.

Enyan Dai, Shijie Zhou, Zhimeng Guo, Suhang Wang

Proceedings of the Learning on Graphs Conference, 2022

Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series.

Enyan Dai, Jie Chen

Proceedings of the Tenth International Conference on Learning Representations, 2022

HP-GMN: Graph Memory Networks for Heterophilous Graphs.

Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs.

Enyan Dai, Zhimeng Guo, Suhang Wang

CoRR, 2021

Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network.

Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai

CoRR, 2021

You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features.

Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang

CoRR, 2021

Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information.

Enyan Dai, Suhang Wang

Proceedings of the WSDM '21, 2021

Labeled Data Generation with Inexact Supervision.

Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs.

Enyan Dai, Charu Aggarwal, Suhang Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Towards Self-Explainable Graph Neural Network.

Enyan Dai, Suhang Wang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

TEST_POSITIVE at W-NUT 2020 Shared Task-3: Joint Event Multi-task Learning for Slot Filling in Noisy Text.

Chacha Chen, Chieh-Yang Huang, Yaqi Hou, Yang Shi, Enyan Dai, Jiaqi Wang

CoRR, 2020

FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information.

Enyan Dai, Suhang Wang

CoRR, 2020

Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository.

Enyan Dai, Yiwei Sun, Suhang Wang

Proceedings of the Fourteenth International AAAI Conference on Web and Social Media, 2020

Unsupervised Image Super-Resolution with an Indirect Supervised Path.

Shuaijun Chen, Zhen Han, Enyan Dai, Xu Jia, Ziluan Liu, Xing Liu, Xueyi Zou, Chunjing Xu, Jianzhuang Liu, Qi Tian

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

TEST_POSITIVE at W-NUT 2020 Shared Task-3: Cross-task modeling.

Chacha Chen, Chieh-Yang Huang, Yaqi Hou, Yang Shi, Enyan Dai, Jiaqi Wang

Proceedings of the Sixth Workshop on Noisy User-generated Text, 2020

2019

Unsupervised Image Super-Resolution with an Indirect Supervised Path.

Zhen Han, Enyan Dai, Xu Jia, Xiaoying Ren, Shuaijun Chen, Chunjing Xu, Jianzhuang Liu, Qi Tian

CoRR, 2019