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The graph attention network (GAT) was introduced by Petar Veličković et al. in 2018. [11] Graph attention network is a combination of a GNN and an attention layer. The implementation of attention layer in graphical neural networks helps provide attention or focus to the important information from the data instead of focusing on the whole data.
In network theory, link prediction is the problem of predicting the existence of a link between two entities in a network. Examples of link prediction include predicting friendship links among users in a social network, predicting co-authorship links in a citation network, and predicting interactions between genes and proteins in a biological network.
Girvan–Newman algorithm; Goal node (computer science) Gomory–Hu tree; Graph bandwidth; Graph edit distance; Graph embedding; Graph isomorphism; Graph isomorphism problem; Graph kernel; Graph neural network; Graph reduction; Graph traversal; GYO algorithm
Networks such as the previous one are commonly called feedforward, because their graph is a directed acyclic graph. Networks with cycles are commonly called recurrent. Such networks are commonly depicted in the manner shown at the top of the figure, where is shown as dependent upon itself. However, an implied temporal dependence is not shown.
Chen has made significant contributions to graph neural networks (GNNs). Chen and his students proposed DGCNN, one of the first graph convolution techniques that can learn a meaningful tensor representation from arbitrary graphs, and showed its deep connection to the Weisfeiler-Lehman algorithm. [12]
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [1] [2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. Artificial ...
[5] [17] The third-order tensor is a suitable methodology to represent a knowledge graph because it records only the existence or the absence of a relation between entities, [17] and for this reason is simple, and there is no need to know a priori the network structure, [15] making this class of embedding models light, and easy to train even if ...
A clique tree or junction tree is a tree of cliques, used in the junction tree algorithm. A chain graph is a graph which may have both directed and undirected edges, but without any directed cycles (i.e. if we start at any vertex and move along the graph respecting the directions of any arrows, we cannot return to the vertex we started from if ...