5 papers
Spiking Local Interaction and Adaptive Complementary Fusion for Spiking Transformer
Dongcheng Zhao, Sicheng Shen, Zhenyu Yang +6
Spiking Transformers model token interactions primarily through spiking self-attention (SSA). However, binary query and key representations map continuous similarities to sparse an…
UniBCI: Towards a Unified Pretrained Model for Invasive Brain-Computer Interfaces
Binjie Hong, Rui Xiong, Liyuan Han +1
Modeling invasive neural spike data is fundamental to advancing high-performance brain-computer interfaces (BCIs). However, existing approaches face critical challenges, including…
Adaptive Runge-Kutta Dynamics for Spatiotemporal Prediction
Xuanle Zhao, Yue Sun, Ziyi Wang +2
Spatiotemporal prediction is important in solving natural problems and processing video frames, especially in weather forecasting and human action recognition. Recent advances atte…
TaiBai: A fully programmable brain-inspired processor with topology-aware efficiency
Qianpeng Li, Yu Song, Xin Liu +6
Brain-inspired computing has emerged as a promising paradigm to overcome the energy-efficiency limitations of conventional intelligent systems by emulating the brain's partitioned…
Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
Learning from interaction is the primary way that biological agents acquire knowledge about their environment and themselves. Modern deep reinforcement learning (DRL) explores a co…