3 papers
cs.LG2026
Active Continual Learning with Metaplastic Binary Bayesian Neural Networks
Kellian Cottart, Théo Ballet, Djohan Bonnet +1
Always-on edge systems must keep learning as conditions change under tight compute budgets and must detect unreliable predictions. Bayesian binary neural networks are attractive in…
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.ET2024
Hardware architecture and routing-aware training for optimal memory usage: a case study
Jimmy Weber, Theo Ballet, Melika Payvand
Efficient deployment of neural networks on resource-constrained hardware demands optimal use of on-chip memory. In event-based processors, this is particularly critical for routing…