The inherent adversarial robustness of analog in-memory computing

Abstract A key challenge for deep neural network algorithms is their vulnerability to adversarial attacks. Inherently non-deterministic compute substrates, such as those based on analog in-memory computing, have been speculated to provide significant adversarial robustness when performing deep neura...

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Bibliographic Details
Main Authors: Corey Lammie, Julian Büchel, Athanasios Vasilopoulos, Manuel Le Gallo, Abu Sebastian
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-56595-2