2 papers
cs.ET2026
Uncertainty-triggered wake-up enables energy-efficient, error-resilient edge AI with memristor front ends
Théo Ballet, Aymen Romdhane, Bruno Lovison-Franco +11
Memristor computing offers a route to low-energy edge AI, but device variability, sensitivity to operating conditions, and system-integration challenges can hinder deployment. Here…
cs.NE2025
Unsupervised local learning based on voltage-dependent synaptic plasticity for resistive and ferroelectric synapses
Nikhil Garg, Ismael Balafrej, Joao Henrique Quintino Palhares +11
The deployment of AI on edge computing devices faces significant challenges related to energy consumption and functionality. These devices could greatly benefit from brain-inspired…