About
Contact & Profiles
A5101470597
Research Areas
- Metallurgy and Material Forming
- Neural Networks and Applications
- Multimodal Machine Learning Applications
- Face and Expression Recognition
- Aluminum Alloy Microstructure Properties
- Advanced Graph Neural Networks
- Complex Network Analysis Techniques
- Bayesian Modeling and Causal Inference
- Video Surveillance and Tracking Methods
- Computational Drug Discovery Methods
- Machine Learning in Materials Science
- Electrochemical Analysis and Applications
- Wireless Signal Modulation Classification
- Human Pose and Action Recognition
- High Temperature Alloys and Creep
- Video Analysis and Summarization
Jilin University
2024
Ningbo University
2024
10.26599/mas.2025.9580007
article
EN
2025-03-01
10.1109/tkde.2024.3397692
article
EN
IEEE Transactions on Knowledge and Data Engineering
2024-05-07
10.1016/j.neucom.2024.128094
article
EN
Neurocomputing
2024-06-22
Despite the recent progress of molecular representation learning, its effectiveness is assumed on close-world assumptions that training and testing graphs are from identical distribution. The open-world test dataset often mixed with out-of-distribution (OOD) samples, where deployed models will struggle to make accurate predictions. misleading estimations molecules' properties in drug screening or design can result tremendous waste wet-lab resources delay discovery novel therapies....
10.1145/3637528.3671785
article
EN
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
2024-08-24
10.1109/cvpr52733.2024.01751
article
EN
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2024-06-16
10.1109/tnse.2024.3498434
article
EN
IEEE Transactions on Network Science and Engineering
2024-01-01
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