Deep Learning for Graphs Has a Long-Standing History. The deep learning for graphs field is rooted in neural networks for graphs research and early 1990s works on Recursive Neural Networks (RecNN) for ...

The field of graph deep learning is still rapidly evolving and many research ideas emerge by standing on the shoulders of giants. To ease the process, DGl-Go is a command-line interface to get started ...

Deep learning on point clouds has attracted increasing attention in the fields of 3D computer vision and robotics. In particular, graph-based point-cloud deep neural networks (DNNs) have demonstrated ...

Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is ...

Following is what you need for this book: For data scientists, machine learning practitioners, researchers delving into graph-based data, and software engineers crafting graph-related applications, ...

We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner. DGI relies on maximizing mutual information between ...

Rebooting AI: Deep learning, meet knowledge graphs Knowledge graphs, the 20-year old hype, may have something to offer there. Written by George Anadiotis, Contributor Nov. 20, 2020 at 7:49 a.m. PT ...