2 papers
cs.AI2025
Enhancing AI System Resiliency: Formulation and Guarantee for LSTM Resilience Based on Control Theory
Sota Yoshihara, Ryosuke Yamamoto, Hiroyuki Kusumoto +1
This paper proposes a novel theoretical framework for guaranteeing and evaluating the resilience of long short-term memory (LSTM) networks in control systems. We introduce "recover…
cs.NE2023
Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks
Ryuji Saiin, Tomoya Shirakawa, Sota Yoshihara +2
In this article, we propose a new paradigm for training spiking neural networks (SNNs), spike accumulation forwarding (SAF). It is known that SNNs are energy-efficient but difficul…