News

Uncovering 'Dark Data' With AI-Driven Knowledge Graphs

Firms that fail to shine light on their dark data risk ceding the high ground in insights and inviting risk exposures lurking ...
Scientific Research Publishing

Agentic AI in Contract Analytics Harnessing Machine Learning for Risk Assessment and Compliance in Government Procurement Contracts ()

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional methods of contract analytics are time-consuming and often inexact, thus ...

Yingjie Technology Applies for Patent on Graph Neural Network, Significantly Enhancing Multi-Robot Collaborative Scheduling Efficiency

Recently, Tianjin Yingjie Technology Development Co., Ltd. announced the application for a patent titled "An Optimization Method for Multi-Robot Collaborative Task Scheduling Based on Graph Neural ...

Xister New Energy Applies for AI Circuit Wiring Patent, Accelerating the Efficiency of Analog Integrated Circuit Design

Shenzhen Xister New Energy Technology Co., Ltd. recently announced that it has applied for a patent titled "An AI-Based Circuit Wiring System, Method, Medium, and Device," with publication number ...

Neo4j unifies real-time transactions and graph analytics at scale

Neo4j also trumpeted the value of graphs as vector databases used in generative artificial intelligence. AI training requires ...
South Africa Today on MSN

Building Smarter Systems at the Intersection of Technology, Research, and Governance

In the era of digital transformation, few professionals are able to bridge large-scale enterprise technology with frontier ...
C&EN

Integrating ESM-2 and Graph Neural Networks with AlphaFold-2 Structures for Enhanced Protein Function Prediction

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
C&EN

GGCRB: A Graph Neural Network Approach for Predicting CircRNA–RBP Interactions Using Structural and Sequence Features

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The interaction between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) plays ...
Phys.org

Common feature between forest fires and neural networks reveals universal framework

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...
Searchenginejournal.com

Google’s New Graph Foundation Model Improves Precision By Up To 40X

Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...
IEEE

GIGNet: A Graph-in-Graph Neural Network for Automatic Modulation Recognition

Abstract: In this paper, we propose a robust end-to-end classification model, Graph-in-Graph Neural Network (GIGNet), for automatic modulation recognition (AMR). In GIGNet, multi-level graph neural ...
GitHub

Missing-Modality-Aware Graph Neural Network for Cancer Classification

MAGNET is implemented in Python 3.10 and is supported on both Linux and Windows. It should work on any operating system that supports Python. The implementation has been tested on both GPU and CPU ...