Latest Articles for Graph Neural Networks

New framework enhances neural networks' ability to handle recursive problems using stack memory.

A new method enhances multi-hop question answering accuracy using local reasoning graphs.

A new model improves predictions for carbon dioxide migration in geological formations.

Researchers enhance drug-target binding predictions with multimodal knowledge graphs.

A look into improving topic modeling through innovative sampling strategies.

A machine learning approach improves predictions of particle dynamics in complex fluids.

This paper presents a novel model for analyzing event data on graph structures.

Graph Neural Networks transform how we analyze time series data for better predictions.

New methods improve the accuracy of nanodevices in medical applications.

A novel approach uses graph neural networks to predict elastic properties efficiently.

Curiosity-driven methods improve exploration strategies in artificial intelligence.

Explore how dynamic graphs capture the evolving nature of relationships.

A new framework balances privacy and utility in graph learning.

Boosting molecular predictions using efficient model techniques.

GPSE improves graph model performance through enhanced encodings and knowledge transfer.

Examining the issues and potential of explainable AI methods.

Examining how differential privacy impacts graph neural networks in medical applications.

A new method improves understanding of predictions in graph regression tasks.

A new method for pinpointing influencers in evolving marketing networks.

New techniques improve breast cancer image analysis and diagnosis accuracy.

New methods create varied datasets for better evaluation of Graph Neural Networks.

This article reviews methods to predict trends in AI and nuclear nonproliferation capabilities.

A new module improves graph structure learning in GNNs for better results.

A new method to analyze urban infrastructure weaknesses and improve city resilience.

This study examines the ReVeal model's effectiveness in detecting code vulnerabilities.

New layer improves molecule behavior predictions in drug development.

A new method improves object state recognition using knowledge graphs.

A novel approach helps detect ALS by analyzing facial movements.

An overview of GNNs, their features, and training dynamics.

A novel approach for accurate landmark detection in heart images using graph structures.

Explore how GNNs improve variable mapping for program comparison and repair.

This study focuses on enhancing GNNs to overcome challenges from biased training data.

New methods improve sound localization using distributed microphone arrays.

Introducing STZINB-GNN, a better model for predicting traffic accidents and uncertainties.

Explore the Node Injection Link Stealing attack and privacy concerns in GNNs.

A new method helps robots decide where to go in partially known areas.

A detailed look at topologically attributed graphs for efficient shape classification.

TimeGNN improves forecasting accuracy using dynamic graphs to capture changing relationships.

Researchers use GNNs to enhance fluid flow simulation efficiency and accuracy.

A novel approach to improve encrypted traffic classification using byte-level analysis.