1 code implementation • 18 Dec 2023 • Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang
Hypergraphs play a pivotal role in the modelling of data featuring higher-order relations involving more than two entities.
no code implementations • 8 Oct 2022 • Ziyuan Ye, Youzhi Qu, Zhichao Liang, Mo Wang, Quanying Liu
The results show that STpGCN significantly improves brain decoding performance compared to competing baseline models; BrainNetX successfully annotates task-relevant brain regions.
1 code implementation • 14 Jul 2022 • Runpeng Hou, Ziyuan Ye, Chengyu Yang, Linhao Fu, Chao Liu, Quanying Liu
Our work offers a benchmark dataset for training deep learning models for capillary image segmentation and provides a potential tool for future capillary research.
no code implementations • 30 Nov 2021 • Xuming Ran, Jie Zhang, Ziyuan Ye, Haiyan Wu, Qi Xu, Huihui Zhou, Quanying Liu
In this study, we propose an integrated framework called Deep Autoencoder with Neural Response (DAE-NR), which incorporates information from ANN and the visual cortex to achieve better image reconstruction performance and higher neural representation similarity between biological and artificial neurons.