Latest Articles for GNNs

Exploring local symmetries to enhance graph-based machine learning methods.

Examining how deep learning improves earthquake prediction accuracy.

A new method improves evolutionary tree construction using deep learning.

A method to clean noisy graphs and enhance GNN performance.

A new approach to transmit graph data effectively by focusing on essential information.

Exploring machine learning techniques for efficient VLSI design partitioning.

New method enhances analysis of complex systems through Symplectic Graph Neural Networks.

This article explores the impact of Massive Activations in attention-based GNNs.

New methods help detect cyberattacks in complex power systems.

Exploring the role of non-autoregressive networks in solving complex optimization problems.

Introducing GSSC, a framework to improve graph learning without traditional message passing.

This research enhances prediction reliability in GNNs through integrated uncertainty quantification.

CrossGR enhances product recommendations across markets using innovative graph technology.

A new method for identifying fake accounts on social networks.

New machine learning techniques improve predictions in polycrystal plasticity.

PropEnc transforms graph metrics into useful node features, enhancing GNN performance.

New methods enhance robotic mapping of indoor spaces using factor graphs and machine learning.

New techniques improve early prediction of chronic health issues using patient data.

New methods enhance object location tracking in dense urban areas.

A new method for improving GNNs in molecular analysis.

DuoGNN enhances graph analysis by separating node interactions for improved performance.

This article discusses techniques for hidden communication with UAVs to avoid detection.

Exploring new ways to combat money laundering through data sharing and machine learning.

A new method improves material property predictions using advanced techniques.

Learn how dual graph approaches enhance data analysis and predictions.

A look into GNNs and GTs and the role of positional encodings.

A new model analyzes social media to identify LGBTQ+ minority stress.

RobustCRF enhances GNN resilience while maintaining performance in real-world applications.

Using galaxies' relationships, a GNN predicts dark matter halo masses more accurately than traditional methods.

A new method predicts dataflow strategies for better GNN processing.

Combining advanced techniques streamlines analog circuit design for better efficiency.

Discover how SDR-GNN improves emotion understanding in conversations.

A new system that tracks objects using multiple camera views in real-time.

A new approach to enhance MILP solutions using graph neural networks.

A new method improves brain blood flow diagnosis and treatment.

Introducing methods that allow models to abstain from uncertain predictions.

Combining timing and relationships for better EEG understanding.

CNA method enhances GNNs by tackling oversmoothing and improving performance.

Exploring the rivalry of knowledge graph models and their effectiveness.

Explore the role of signed graphs in data science and advancements in GNNs.