Enyan Dai
Orcid: 0000-0001-9715-0280
According to our database1,
Enyan Dai
authored at least 34 papers
between 2019 and 2024.
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Bibliography
2024
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability.
Mach. Intell. Res., December, 2024
IEEE Trans. Software Eng., July, 2024
CoRR, 2024
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection.
CoRR, 2024
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
2023
Neurocomputing, December, 2023
Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information.
IEEE Trans. Knowl. Data Eng., July, 2023
Proceedings of the ACM Web Conference 2023, 2023
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.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
2022
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022
Proceedings of the Learning on Graphs Conference, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the IEEE International Conference on Data Mining, 2022
2021
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network.
CoRR, 2021
You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features.
CoRR, 2021
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information.
Proceedings of the WSDM '21, 2021
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.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
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.
CoRR, 2020
FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information.
CoRR, 2020
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository.
Proceedings of the Fourteenth International AAAI Conference on Web and Social Media, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the Sixth Workshop on Noisy User-generated Text, 2020
2019