Latest Articles for GNNs

Discover how Routing-by-Memory enhances MLP performance in graph neural networks.

DeepGate3 enhances circuit design understanding and scalability with innovative model architecture.

A new approach enhances predictions for new items using unique interaction patterns.

Using machine learning to enhance the interpretability of molecular simulations.

A novel method enhances GNN performance with noisy data.

Establishing a benchmark to evaluate fairness in graph learning methods.

New methods enhance uncertainty estimates in GNNs for modeling material energies.

A new approach improves GNN reasoning capabilities for complex relationship tasks.

scTransNet framework improves understanding of gene interactions using single-cell RNA data.

Wav2graph creates knowledge graphs from spoken language for improved AI understanding.

A new method aims to enhance recommendations in changing data environments.

New GNN models enhance molecular representation for better predictions in science.

This article discusses a new method for classifying graphs using basic structural features.

AI methods are changing how scientists predict molecular properties for various applications.

A new method improves link prediction in graph neural networks using LLwLC.

A novel method to enhance data discovery and analysis for better predictions.

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.