5 papers
Beyond Runtime Enforcement: Shield Synthesis as Defensibility Analysis for Adversarial Networks
Achraf Hsain, Sultan Almuhammadi
Shielded reinforcement learning is typically presented as a runtime safety mechanism that compiles temporal-logic specifications into automata restricting an agent's actions. We ar…
Adversarial Vulnerability Transcends Computational Paradigms: Feature Engineering Provides No Defense Against Neural Adversarial Transfer
Achraf Hsain, Ahmed Abdelkader, Emmanuel Baldwin Mbaya +1
Deep neural networks are vulnerable to adversarial examples--inputs with imperceptible perturbations causing misclassification. While adversarial transfer within neural networks is…
Point Cloud to Mesh Reconstruction: Methods, Trade-offs, and Implementation Guide
Fatima Zahra Iguenfer, Achraf Hsain, Hiba Amissa +1
Reconstructing meshes from point clouds is a fundamental task in computer vision with applications spanning robotics, autonomous systems, and medical imaging. Selecting an appropri…
Tiny Machine Learning for Real-Time Aquaculture Monitoring: A Case Study in Morocco
Achraf Hsain, Yahya Zaki, Othman Abaakil +2
Aquaculture, the farming of aquatic organisms, is a rapidly growing industry facing challenges such as water quality fluctuations, disease outbreaks, and inefficient feed managemen…
Quantum Generative Models for Computational Fluid Dynamics: A First Exploration of Latent Space Learning in Lattice Boltzmann Simulations
Achraf Hsain, Fouad Mohammed Abbou
This paper presents the first application of quantum generative models to learned latent space representations of computational fluid dynamics (CFD) data. While recent work has exp…