3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.LG2025
GnnXemplar: Exemplars to Explanations -- Natural Language Rules for Global GNN Interpretability
Burouj Armgaan, Eshan Jain, Harsh Pandey +2
Graph Neural Networks (GNNs) are widely used for node classification, yet their opaque decision-making limits trust and adoption. While local explanations offer insights into indiv…
cs.LG2023★ 3 cited
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…
cs.LG2023
Empowering Counterfactual Reasoning over Graph Neural Networks through Inductivity
Samidha Verma, Burouj Armgaan, Sourav Medya +1
Graph neural networks (GNNs) have various practical applications, such as drug discovery, recommendation engines, and chip design. However, GNNs lack transparency as they cannot pr…