STAREAST

An Introduction to Property Graph Query Language

A set of vertices with each vertex having zero or more labels and zero or more properties/attributes. A set of edges with each edge being directed from one vertex to another vertex. Each edge has zero ...
C&EN

EOSnet: Embedded Overlap Structures for Graph Neural Networks in Predicting Material Properties

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph Neural Networks (GNNs) have emerged as powerful tools for predicting material ...
marktechpost

Graph Generative Pre-trained Transformer (G2PT): An Auto-Regressive Model Designed to Learn Graph Structures through Next-Token Prediction

Graph generation is an important task across various fields, including molecular design and social network analysis, due to its ability to model complex relationships and structured data. Despite ...
Oak Ridge National Lab

Derivative-based pre-training of graph neural networks for materials property predictions

While pre-training has transformed many fields in deep learning tremendously, its application to three-dimensional crystal structures and materials science remains limited and under-explored. In ...
IEEE

Extracting Graphs Properties with Semantic Joins

Abstract: This paper proposes an approach to querying a relational database $\mathcal{D}$ and a graph G taken together in SQL. We introduce a semantic extension of joins across $\mathcal{D}$ and G ...
Scientific Research Publishing

On the Line Graph of the Complement Graph for the Ring of Gaussian Integers Modulo n ()

The line graph for the complement of the zero divisor graph for the ring of Gaussian integers modulo n is studied. The diameter, the radius and degree of each vertex are determined. Complete ...
marktechpost

Microsoft Researchers Propose ViSNet: An Equivariant Geometry-Enhanced Graph Neural Network for Predicting Molecular Properties and Simulating Molecular Dynamics

Researchers from Microsoft attempt to solve the challenge faced in predicting molecular properties and simulating molecular dynamics by presenting a method, ViSNet, that results in more accurate ...