Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Like many of us, [Tim]’s seen online videos of circuit sculptures containing illuminated LED filaments. Unlike most of us, however, he went a step further by using graph theory to design glowing ...

Abstract: The nature of heterophilous graphs is significantly different from that of homophilous graphs, which causes difficulties in early graph neural network (GNN) models and suggests aggregations ...

This repository contains code for Talk like a Graph: Encoding Graphs for Large Language Models and Let Your Graph Do the Talking: Encoding Structured Data for LLMs. @inproceedigs{fatemi2024talk, ...

I grew up in the Dallas suburb of Lewisville when it had more gun racks than yoga mats. In elementary school, I was one of two black kids in the entire building. It was the early 1980s: faded ...

Abstract: Knowledge graph embedding is efficient method for reasoning over known facts and inferring missing links. Existing methods are mainly triplet-based or graph-based. Triplet-based approaches ...

Does string theory—the controversial “theory of everything” from physics—tell us anything about consciousness and the human brain? If you're enjoying this article, consider supporting our ...