3 papers
cs.NE2026
SuperNeuroMAT: An Efficient Matrix-based Simulator for Spiking Neural Networks
Prasanna Date, Kevin Zhu, Shruti Kulkarni +12
Spiking neural networks (SNNs) offer a promising pathway to energy-efficient AI and brain-inspired computing. However, their widespread adoption is hindered by a lack of fast, acce…
cs.NE2026
Neuromorphic Parameter Estimation for Power Converter Health Monitoring Using Spiking Neural Networks
Hyeongmeen Baik, Hamed Poursiami, Maryam Parsa +1
Always-on converter health monitoring demands sub-mW edge inference, a regime inaccessible to GPU-based physics-informed neural networks. This work separates spiking temporal proce…
cs.ET2024
Transductive Spiking Graph Neural Networks for Loihi
Shay Snyder, Victoria Clerico, Guojing Cong +4
Graph neural networks have emerged as a specialized branch of deep learning, designed to address problems where pairwise relations between objects are crucial. Recent advancements…