Describing exciting new opportunities for utilizing robust graph representations of data with common machine learning algorithms, this book demonstrates and investigates these novel techniques through ...

Graphs are pictorial representations of numbers. Therefore, at the least, we should expect that the representation of the numbers be proportional to the numbers themselves. Unfortunately, this is not ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...