Yizhen Zheng
Orcid: 0000-0002-3540-8845
According to our database1,
Yizhen Zheng
authored at least 20 papers
between 2021 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
IEEE Trans. Neural Networks Learn. Syst., July, 2024
Pattern Recognit., April, 2024
Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective.
Inf. Sci., February, 2024
IEEE Intell. Syst., 2024
Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials.
CoRR, 2024
A new attention-based deep metric model for crop type mapping in complex agricultural landscapes using multisource remote sensing data.
Int. J. Appl. Earth Obs. Geoinformation, 2024
2023
CoRR, 2023
CoRR, 2023
Proceedings of the ACM Web Conference 2023, 2023
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the IEEE International Conference on Data Mining, 2023
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Proceedings of the IEEE International Conference on Data Mining, 2022
2021
Heterogeneous Graph Attention Network for Small and Medium-Sized Enterprises Bankruptcy Prediction.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021
Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021