Abstract: The growth of machine learning (ML) has revealed model vulnerabilities to adversarial attacks, where small data perturbations degrade performance. Classical defenses often struggle, ...

Abstract: Analog in-memory computing is a next-generation computing paradigm that promises fast, parallel, and energy-efficient deep learning training and transfer learning (TL). However, achieving ...