3 citations · 9 across the 8 of their papers we have counts for
4 papers · 1 filter
DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization
Aritra Bhowmick, Mert Kosan, Zexi Huang +2
Graph clustering is a fundamental and challenging task in the field of graph mining where the objective is to group the nodes into clusters taking into consideration the topology o…
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
Mert Kosan, Samidha Verma, Burouj Armgaan +4
Numerous explainability methods have been proposed to shed light on the inner workings of GNNs. Despite the inclusion of empirical evaluations in all the proposed algorithms, the i…
Link Prediction without Graph Neural Networks
Zexi Huang, Mert Kosan, Arlei Silva +1
Link prediction, which consists of predicting edges based on graph features, is a fundamental task in many graph applications. As for several related problems, Graph Neural Network…
Robust Ante-hoc Graph Explainer using Bilevel Optimization
Kha-Dinh Luong, Mert Kosan, Arlei Lopes Da Silva +1
Explaining the decisions made by machine learning models for high-stakes applications is critical for increasing transparency and guiding improvements to these decisions. This is p…