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Open access 2026

SHAP-GSD: Temporal Multi-Granular Explanation Method for Graph Neural Networks in Network Intrusion Detection

SHapley Additive exPlanations on Graph-Structured Data (SHAP-GSD), a temporally constrained Shapley framework that decomposes each alert into three attribution layers, is presented, the first Shapley formulation to simultaneously deliver temporally faithful, multi-granularity attribution across all three evidence dimen...

Riko Luša, Damir Pintar, Mihaela Vranić · 0 citations
Review Open access Aug 2026

Explicitness in SMILES representation via ExACT: improved tokenization for aqueous solubility prediction

The representation of molecular structure in textual form plays a central role in data-driven cheminformatics, not just for deep learning models that often rely on sequence-based inputs, but also for classic machine learning pipelines which are still relevant in this field. The Simplified Molecular Input Line Entry S...

D. Begušić, D. Pintar, Zlatko Smole et al. · 0 citations

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