Deep graph clustering has recently received significant attention due to its ability to enhance
the representation learning capabilities of models in unsupervised scenarios. Nevertheless …

In this article, a modified mutual information maximization (InfoMax) framework, named
channel capacity maximization (CapMax), is proposed and applied to learn informative …

Graph data is an important data type for representing the relationships between individuals,
and many research works are conducted based on graph data. In the real-world, graph data …

Real-world networks are always dynamic. Dynamic network representation learning
represents nodes in a network as low-dimensional, dense, real-valued vectors while …

Community detection is the task of discovering groups of nodes sharing similar patterns
within a network. With recent advancements in deep learning, methods utilizing graph …

Recently, deep clustering methods have become a hot research topic, as they fuse deep
learning and clustering by utilizing deep neural networks like autoencoders to learn effective …

Community detection is the task of discovering groups of nodes sharing similar patterns
within a network. With recent advancements in deep learning, methods utilizing graph …