Minghua Deng

TGNN: A Joint Semi-supervised Framework for Graph-level Classification

2022

This paper studies semi-supervised graph classification, a crucial task with a wide range of applications in social network analysis and bioinformatics. Recent works typically adopt graph neural networks to learn graph-level representations for classification, failing …

Mutual Nearest Neighbor Contrast and Hybrid Prototype Self-Training for Universal Domain Adaptation

2022 · Proceedings of the AAAI Conference on Artificial Intelligence

Universal domain adaptation (UniDA) aims to transfer knowledge learned from a labeled source domain to an unlabeled target domain under domain shift and category shift. Without prior category overlap information, it is challenging to simultaneously …