65 citations · 79 across the 4 of their papers we have counts for
4 papers
Multimodal Graph Representation Learning with Dynamic Information Pathways
Xiaobin Hong, Mingkai Lin, Xiaoli Wang +2
Multimodal graphs, where nodes contain heterogeneous features such as images and text, are increasingly common in real-world applications. Effectively learning on such graphs requi…
Rethinking Multi-view Representation Learning via Distilled Disentangling
Guanzhou Ke, Bo Wang, Xiaoli Wang +1
Multi-view representation learning aims to derive robust representations that are both view-consistent and view-specific from diverse data sources. This paper presents an in-depth…
Disentangling Multi-view Representations Beyond Inductive Bias
Guanzhou Ke, Yang Yu, Guoqing Chao +3
Multi-view (or -modality) representation learning aims to understand the relationships between different view representations. Existing methods disentangle multi-view representatio…
A Clustering-guided Contrastive Fusion for Multi-view Representation Learning
Guanzhou Ke, Guoqing Chao, Xiaoli Wang +3
The past two decades have seen increasingly rapid advances in the field of multi-view representation learning due to it extracting useful information from diverse domains to facili…