R Street Institute

Post-Quantum Cryptography Migration in the United States: Managing Risk and Advancing Cyber Readiness in Critical Infrastructure

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AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
financefeeds

Best Tools for Discovering New Crypto Projects

DexScreener tracks every trading pair across more than 100 blockchain networks for free, surfacing new token pairs within minutes of liquidity going live on decentralized exchanges. Dune Analytics ...
IEEE

Anomaly Detection Over Multi-Relational Graphs Using Graph Structure Learning and Multi-Scale Meta-Path Graph Aggregation

Abstract: Graph Neural Networks (GNNs) have recently achieved remarkable success in various learning tasks involving graph-structured data. However, their application to multi-relational graph anomaly ...
Wired

Amazon Thinks the Future of Data Centers Depends on a Technical Problem It Just Solved

The tech giant says a breakthrough in data center networking has dramatically accelerated the flow of information through its massive cloud infrastructure. The new technology hinges on a “quasi-random ...
Redmond Magazine

Microsoft Sentinel Adds Custom Graphs for Security Data Visualization

Microsoft Sentinel adds custom graphs to visualize security data and attack relationships. Graph-based analysis helps detect threats, map attack paths, and identify anomalies. Fabric-powered ...
LinkedIn

Beyond the Neo4j Graph RAG tutorial

Graphs are a data structure that has gained a lot of traction in recent years. It is one of the most, if not the most flexible data structures, well adapted for solutions requiring speed and depth.
WatersTechnology

Knowledge graphs, data quality, and reuse form Bloomberg’s AI strategy

Have you ever gone to sleep with visions of gelatin bubbles dancing in your head? What about information on 70 million financial securities and 40,000 data fields? Marvin Ward knows what both are like ...
Time

6 Graphs That Show Where the U.S. Leads China on AI—and Where It Doesn’t

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techxplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
EurekAlert!

A survey of geometric graph neural networks: data structures, models and applications

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...
Nature

NMR data processing, visualization, analysis and structure calculation with NMRFx

NMR spectroscopy is applied in many scientific disciplines to derive chemical, structural, and dynamical insights into molecular systems. The utility of the technique depends on robust computational ...