To handle the above two challenges, we propose a novel Graph Embedding Contrastive Multi-modal Clustering network (GECMC), which treats the representation learning and multi-modal clustering as two ...

Model Explorer offers an intuitive and hierarchical visualization of model graphs. It organizes model operations into nested layers, enabling users to dynamically expand or collapse these layers. It ...

We consider the problem of representation learning for graph data. Given images are special cases of graphs with nodes lie on 2D lattices, graph embedding tasks have a natural correspondence with ...