3 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.ET2026
Forward-only learning in memristor arrays with month-scale stability
Adrien Renaudineau, Mamadou Hawa Diallo, Théo Dupuis +12
Turning memristor arrays from efficient inference engines into systems capable of on-chip learning has proved difficult. Weight updates have a high energy cost and cause device wea…
cs.AR2023
Sparq: A Custom RISC-V Vector Processor for Efficient Sub-Byte Quantized Inference
Théo Dupuis, Yoan Fournier, MohammadHossein AskariHemmat +4
Convolutional Neural Networks (CNNs) are used in a wide range of applications, with full-precision CNNs achieving high accuracy at the expense of portability. Recent progress in qu…