2 citations · 2 across the 4 of their papers we have counts for
5 papers
BCIJelly: An integrated ecosystem for brain-computer interface research
Liyuan Han, Xinrui Yang, Tianyu Zheng +12
Brain-computer interface (BCI) research relies on multistage computational pipelines, yet progress remains constrained by fragmented data formats, heterogeneous decoder implementat…
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…
Multiscale fusion enhanced spiking neural network for invasive BCI neural signal decoding
Yu Song, Liyuan Han, Bo Xu +1
Brain-computer interfaces (BCIs) are an advanced fusion of neuroscience and artificial intelligence, requiring stable and long-term decoding of neural signals. Spiking Neural Netwo…
Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks
Tianyu Zheng, Liyuan Han, Tielin Zhang
Spiking neural networks (SNNs) are gaining popularity in the computational simulation and artificial intelligence fields owing to their biological plausibility and computational ef…
ODE-based Recurrent Model-free Reinforcement Learning for POMDPs
Xuanle Zhao, Duzhen Zhang, Liyuan Han +2
Neural ordinary differential equations (ODEs) are widely recognized as the standard for modeling physical mechanisms, which help to perform approximate inference in unknown physica…