10 citations · 24 across the 6 of their papers we have counts for
6 papers
Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli
Liwei Huang, Zhengyu Ma, Liutao Yu +2
Deep neural networks (DNNs) are widely used models for investigating biological visual representations. However, existing DNNs are mostly designed to analyze neural responses to st…
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
Chenlin Zhou, Han Zhang, Zhaokun Zhou +5
Deep spiking neural networks (SNNs) have drawn much attention in recent years because of their low power consumption, biological rationality and event-driven property. However, sta…
Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse
Liwei Huang, Zhengyu Ma, Liutao Yu +2
Deep artificial neural networks (ANNs) play a major role in modeling the visual pathways of primate and rodent. However, they highly simplify the computational properties of neuron…
Deep Auto-encoder with Neural Response
Xuming Ran, Jie Zhang, Ziyuan Ye +4
Artificial neural network (ANN) is a versatile tool to study the neural representation in the ventral visual stream, and the knowledge in neuroscience in return inspires ANN models…
Bigeminal Priors Variational auto-encoder
Xuming Ran, Mingkun Xu, Qi Xu +2
Variational auto-encoders (VAEs) are an influential and generally-used class of likelihood-based generative models in unsupervised learning. The likelihood-based generative models…
A Two-stream End-to-End Deep Learning Network for Recognizing Atypical Visual Attention in Autism Spectrum Disorder
Jin Xie, Longfei Wang, Paula Webster +4
Eye movements have been widely investigated to study the atypical visual attention in Autism Spectrum Disorder (ASD). The majority of these studies have been focused on limited eye…