Publications
A collection of my research work.
KoopSTD: reliable similarity analysis between dynamical systems via approximating Koopman spectrum with timescale decoupling
Shimin Zhang†, Ziyuan Ye†, Yinsong Yan, Zeyang Song, Yujie Wu, Jibin Wu (equal contribution)†
International Conference on Machine Learning (ICML) 2025
A metric for measuring dynamical similarity between (neural/dynamical) systems by approximating the Koopman spectrum with timescale decoupling and spectral residual control.
Hypergraph transformer for semi-supervised classification
Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2024
A novel hypergraph representation learning framework, HyperGraph Transformer (HyperGT), which leverages a Transformer-based architecture to capture global correlations among all nodes and hyperedges in hypergraphs.
TUN-GCA: A Novel Approach for Organ Segmentation in Nasopharyngeal Carcinoma CT Images
Wenxin Che, Penghui Du, Rihan Huang, Quanying Liu, Youzhi Qu, Ziyuan Ye‡
IJCAI - Workshop on HBAI 2024
A three-stage framework, TransUNet with Gradually Converging Attention (TUN-GCA), for precise organ segmentation in nasopharyngeal carcinoma CT images.
SAME: Uncovering GNN black box with structure-aware shapley-based multipiece explanations
Ziyuan Ye†, Rihan Huang†, Qilin Wu, Quanying Liu (equal contribution)†
Advances in Neural Information Processing Systems (NeurIPS) 2023
A post-hoc explanation method for graph neural networks (GNNs) that uncovers structure-aware feature interactions using a Shapley-based multipiece explanation approach.
Explainable fMRI-based brain decoding via spatial temporal-pyramid graph convolutional network
Ziyuan Ye, Youzhi Qu, Zhichao Liang, Mo Wang, Quanying Liu
Human Brain Mapping 2023
A biologically inspired architecture, Spatial Temporal-pyramid Graph Convolutional Network (STpGCN), to capture the spatial–temporal graph representation of functional brain activities for explainable fMRI-based brain decoding.
Immunofluorescence capillary imaging segmentation: cases study
Runpeng Hou, Ziyuan Ye, Chengyu Yang, Linhao Fu, Chao Liu, Quanying Liu
ACM International Conference on Multimedia (ACM MM) 2022
A benchmark dataset, named IFCIS-155, consisting of 155 2D capillary images with segmentation boundaries and vessel fillings annotated by biomedical experts, and 19 large-scale, high-resolution 3D capillary images for immunofluorescence capillary imaging segmentation.
Deep auto-encoder with neural response
Xuming Ran, Jie Zhang, Ziyuan Ye, Haiyan Wu, Qi Xu, Huihui Zhou, Quanying Liu
arXiv 2021
An integrated framework called Deep Autoencoder with Neural Response (DAE-NR), which incorporates information from artificial neural networks (ANN) and the visual cortex to achieve better image reconstruction performance and higher neural representation similarity between biological and artificial neurons.
Region-focused memetic algorithms with smart initialization for real-world large-scale waste collection problems
Wenxing Lan†, Ziyuan Ye†, Peijun Ruan†, Jialin Liu, Peng Yang, Xin Yao (equal contribution)†
IEEE Transactions on Evolutionary Computation 2021
A region-focused memetic algorithm with smart initialization for solving real-world large-scale waste collection vehicle routing problems (WCVRPs).
Fluorination enhances NIR-II fluorescence of polymer dots for quantitative brain tumor imaging
Ye Liu, Jinfeng Liu, Dandan Chen, Xiaosha Wang, Zhe Zhang, Yicheng Yang, Lihui Jiang, Weizhi Qi, Ziyuan Ye, Shuqing He, others
Angewandte Chemie 2020
A fluorination strategy for semiconducting polymers is described for the development of highly bright second near-infrared region (NIR-II) probes, enabling quantitative brain tumor imaging.
Air pollutants prediction in shenzhen based on arima and prophet method
Ziyuan Ye
E3S Web of Conferences 2019
A hybrid model based on ARIMA and Prophet method for predicting air pollutants in Shenzhen by mixing time and space relationships.