4 papers
KAN KAN Buff Signed Graph Neural Networks?
Muhieddine Shebaro, Jelena TeÅ¡iÄ
Graph Representation Learning aims to create effective embeddings for nodes and edges that encapsulate their features and relationships. Graph Neural Networks (GNNs) leverage neura…
Scaling Frustration Index and Corresponding Balanced State Discovery for Real Signed Graphs
Muhieddine Shebaro, Jelena TeÅ¡iÄ
Structural balance modeling for signed graph networks presents how to model the sources of conflicts. The state-of-the-art focuses on computing the frustration index of a signed gr…
ABCD: Algorithm for Balanced Component Discovery in Signed Networks
Muhieddine Shebaro, Jelena TeÅ¡iÄ
The largest balanced element in signed graphs plays a vital role in helping researchers understand the fundamental structure of the graph, as it reveals valuable information about…
GraphC: Parameter-free Hierarchical Clustering of Signed Graph Networks v2
Muhieddine Shebaro, Lucas Rusnak, Martin Burtscher +1
Spectral clustering methodologies, when extended to accommodate signed graphs, have encountered notable limitations in effectively encapsulating inherent grouping relationships. Re…