Context Graphs: AI's Trillion Dollar Opportunity Solved Years Back in CapMarkets

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IEEE

A Flexible Diffusion Convolution for Graph Neural Networks

Abstract: Graph Neural Networks (GNNs) have been gaining more attention due to their excellent performance in modeling various graph-structured data. However, most of the current GNNs only consider ...
Hosted on MSN

The most graphically demanding PC games

Whenever the newest and most competent computer components are released to the public, so are the video games that fully utilize their potential. With hardware manufacturers pivoting their ...
DualShockers

10 Most Graphically Impressive Games Of The 2010s

Jake Valentine is a Staff Writer at DualShockers with more than two decades of experience covering the video game industry. Since 2004, he has written about games across news, reviews, guides, lists, ...
DualShockers

10 Most Graphically Impressive Games Of The 1990s

Adam Braunstein is a Staff Writer at DualShockers who has been covering games professionally since 2019. He primarily writes lists and features, with a focus on RPGs, JRPGs, action-adventure games, VR ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

Long noncoding RNAs (lncRNAs) regulate physiological processes via interactions with macromolecules such as miRNAs, proteins, and genes, forming disease-associated regulatory networks. However, ...
IEEE

Distributed Photovoltaic Power Prediction Based on Spatio-Temporal Diffusion Graph Convolution with Dynamic Graph Networks

Abstract: In order to solve the problem that it is difficult to obtain complete and effective historical power data from the power grid and unable to make full use of the spatio-temporal correlation ...