IEEE

Learning Developmental Age From 3D Infant Kinetics Using Adaptive Graph Neural Networks

Abstract: Reliable methods for the neurodevelopmental assessment of infants are essential for early detection of problems that may need prompt interventions. Spontaneous motor activity, or ‘kinetics’, ...
C&EN

Multilevel Fusion Graph Neural Network for Molecule Property Prediction

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...
C&EN

Density of States Prediction by a Metric-Optimized Equivariant Graph Neural Network

State Key Laboratory of Green Chemical Engineering and Industrial Catalysis, Centre for Computational Chemistry and Research Institute of Industrial Catalysis, East China University of Science and ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
Searchenginejournal.com

Merging SEO And Content Using Your Knowledge Graph To AI-Proof Content

To stay visible in AI search, your content must be machine-readable. Schema markup and knowledge graphs help you define what your brand is known for. New AI platforms, powered by generative ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
IEEE

New Approaches for Network Topology Optimization Using Deep Reinforcement Learning and Graph Neural Network

Abstract: The exponential growth in Internet-connected devices has escalated the demand for optimized network topologies to ensure high performance. Traditional optimization methods often fall short ...