From the 1 of 17 linked papers with an AI index.
17 papers
AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning
Shengyang Li, Yiting Dong, Liuyang Song +5
Federated learning enables collaborative model training across distributed edge devices while strictly preserving data privacy. To facilitate practical deployment on resource-const…
Latency Coding for Efficient and Low-Latency Deep Spiking Neural Networks
Yi Lu, Jianhao Ding, Zhaofei Yu
The paper introduces latency coding, an extension of time‑to‑first‑spike coding, and a training framework using backpropagation through time to build deep spiking neural networks t…
Error Amplification Limits ANN-to-SNN Conversion in Continuous Control
Zijie Xu, Zihan Huang, Yiting Dong +3
Spiking Neural Networks (SNNs) can achieve competitive performance by converting already existing well-trained Artificial Neural Networks (ANNs), avoiding further costly training.…
Uncertainty-Aware Token Importance Estimation in Spiking Transformers
Wenxuan Liu, Zecheng Hao, Tong Bu +2
Spiking transformers have shown strong potential for neuromorphic vision, yet their token processing across multiple spiking steps still introduces substantial redundancy and infer…
GemS-T: Multi-Dimensional Grouping for Ultra-High Energy Efficiency in Spiking Transformer
Zecheng Hao, Shenghao Xie, Kang Chen +3
Spiking Neural Networks (SNNs) offer superior energy efficiency over Artificial Neural Networks (ANNs). However, they encounter significant deficiencies in training and inference m…
PredNext: Explicit Cross-View Temporal Prediction for Unsupervised Learning in Spiking Neural Networks
Yiting Dong, Jianhao Ding, Zijie Xu +3
Spiking Neural Networks (SNNs), with their temporal processing capabilities and biologically plausible dynamics, offer a natural platform for unsupervised representation learning.…