34 citations · 36 across the 2 of their papers we have counts for
3 papers
cs.SD2023★ 34 cited
TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification
Meng Liu, Ke Liang, Dayu Hu +6
Audiovisual data is everywhere in this digital age, which raises higher requirements for the deep learning models developed on them. To well handle the information of the multi-mod…
cs.LG2023★ 2 cited
Reinforcement Graph Clustering with Unknown Cluster Number
Yue Liu, Ke Liang, Jun Xia +5
Deep graph clustering, which aims to group nodes into disjoint clusters by neural networks in an unsupervised manner, has attracted great attention in recent years. Although the pe…
cs.AI2023
Structure Guided Multi-modal Pre-trained Transformer for Knowledge Graph Reasoning
Ke Liang, Sihang Zhou, Yue Liu +3
Multimodal knowledge graphs (MKGs), which intuitively organize information in various modalities, can benefit multiple practical downstream tasks, such as recommendation systems, a…