Michalis Vazirgiannis

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

A novel method for predicting protein functions using descriptive text instead of labels.

IGNNet aims to provide clear explanations for machine learning predictions.

A new model enhances neural networks using graph structures for improved performance.

A new model reveals insights into positive and negative relationships in networks.

Study shows pseudo-code enhances LLM performance on graph tasks.

Exploring a new dataset of Bitcoin transactions for deeper insights.

Learn how CGSOs enhance graph analysis by measuring node importance.

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

Learn how Gaussian Mixture Models enhance GNN performance through data augmentation.