A graph neural network (GNN) belongs to a class of artificial neural networks for processing data that can be represented as graphs. In the more general...

A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce...

replaced with a strictly feedforward neural network, while an infinite impulse recurrent network is a directed cyclic graph that cannot be unrolled. Additional...

social networks such as LinkedIn and Facebook. Recent developments in data science and machine learning, particularly in graph neural networks and representation...

neural networks, marking a departure from the typical focus on learning mappings between finite-dimensional Euclidean spaces or finite sets. Neural operators...

The Open Neural Network Exchange (ONNX) [ˈɒnɪks] is an open-source artificial intelligence ecosystem of technology companies and research organizations...

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...

types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate...

viewed as a message passing algorithm which also connects it to graph neural networks. This is the place where the aforementioned two variants of the...

methods based on neural networks with representation learning. The adjective "deep" refers to the use of multiple layers in the network. Methods used can...