Abstract: Knowledge graph embedding has emerged as a fundamental technique to represent entities and relationships in knowledge graphs within low-dimensional vector spaces. Among these methods, ...

Nature speaks to theoretical physicists to explore the real theories that inspired the hit series. Warning: contains spoilers ...

Multi-electrode arrays (MEAs) provide a noninvasive interface with sub-millisecond temporal resolution and long-term, ...

Abstract: We focus on graph classification using a graph neural network (GNN) model that precomputes node features using a bank of neighborhood aggregation graph operators arranged in parallel. These ...

This repository is the implementation of the following paper: Theoretical Insights into Line Graph Transformation on Graph Learning. This project is built on the BREC dataset which includes 400 pairs ...