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K. Amrouche

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Open access 2026

Filter Spectral Efficiency (FSE): Structured Network Pruning via Inter-Layer Spectral Coupling

Structured filter pruning is an effective approach for reducing the computational cost of deep neural networks while preserving efficient deployment on standard hardware. However, most existing pruning methods evaluate filters independently, overlooking the inter-layer spectral coupling between consecutive layers, whil...

Soumia Laroui, H. Seba, K. Amrouche et al. · 0 citations
Open access Jun 2026

Ensemble Deep Learning for the Classification of Strategic Crops Using Sentinel-2 Time Series

Reliable and up-to-date information on crop distribution is essential for ensuring food security in the face of rapid population growth and climate change, and with recent advancements in remote sensing and artificial intelligence, large-scale analyses of agricultural landscapes can now be performed more quickly and ac...

Yacine Ait Ali Yahia, K. Amrouche, Abir Safta · 0 citations
Preprint Aug 2026

Amortised Post-Hoc Explanation with Exact Preservation for Dynamic Graph Anomaly Detectors

Anomaly detection in dynamic graphs underpins financial fraud analysis, intrusion detection, and platform integrity, where automated decisions require human-interpretable justifications. StrGNN, the strongest performer in recent benchmarks, produces no explanation: when an edge is flagged, the analyst receives only a s...

Iyad Assaad Nekka, H. Seba, Walid Khaled Hidouci et al. · 0 citations
Preprint Aug 2026

Dual Spatial-Temporal Attribution: Architecture-Aligned Post-Hoc Explainability for Recurrent Graph Anomaly Detection

X-AddGraph is presented, a strictly post-hoc explainability framework built on a Dual Spatial-Temporal Attribution (DSTA) mechanism whose three components are each aligned with one of AddGraph's architectural modules: a gradient-based relevance attribution over the current adjacency structure (spatial), a direct readin...

Iyad Assaad Nekka, H. Seba, Khaled Walid Hidouci et al. · 0 citations

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