Secure Multiparty Learning from Aggregation of Locally Trained Models. - Xu Ma; Cunmei Ji; Xiaoyu Zhang 010; Jianfeng Wang 001; Jin Li 002; Kuan-Ching Li (ML4CS, 2019)

Secure multiparty learning from the aggregation of locally trained models. - Xu Ma; Cunmei Ji; Xiaoyu Zhang 010; Jianfeng Wang 001; Jin Li 002; Kuan-Ching Li; Xiaofeng Chen 001 (J. Netw. Comput. Appl., 2020)

ICNNMDA: An Improved Convolutional Neural Network for Predicting MiRNA-Disease Associations. - Rui-Kang Ni; Zhen Gao; Cunmei Ji (ICIC (3), 2021)

AEMDA: inferring miRNA-disease associations based on deep autoencoder. - Cunmei Ji; Zhen Gao; Xu Ma; Qing-Wen Wu; Jian-Cheng Ni 001; Chunhou Zheng 001 (Bioinform., 2021)

GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder. - Lei Li; Yu-Tian Wang; Cunmei Ji; Chun-Hou Zheng 001; Jian-Cheng Ni 001; Yan-Sen Su (PLoS Comput. Biol., 2021)

A Unified Graph Attention Network Based Framework for Inferring circRNA-Disease Associations. - Cunmei Ji; Zhi-Hao Liu; Li-Juan Qiao; Yu-Tian Wang; Chun-Hou Zheng 001 (ICIC (3), 2022)

Cell Classification Based on Stacked Autoencoder for Single-Cell RNA Sequencing. - Rong Qi; Chun-Hou Zheng 001; Cunmei Ji; Ning Yu; Jian-Cheng Ni 001; Yu-Tian Wang (ICIC (2), 2022)

GCNMFCDA: A Method Based on Graph Convolutional Network and Matrix Factorization for Predicting circRNA-Disease Associations. - Dian-Xiao Wang; Cunmei Ji; Yu-Tian Wang; Lei Li; Jian-Cheng Ni 001; Bin Li (ICIC (2), 2022)

A Semi-Supervised Learning Method for MiRNA-Disease Association Prediction Based on Variational Autoencoder. - Cunmei Ji; Yutian Wang; Zhen Gao; Lei Li; Jiancheng Ni 001; Chunhou Zheng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

An End-to-End Deep Hybrid Autoencoder Based Method for Single-Cell RNA-Seq Data Analysis. - Cunmei Ji; Ning Yu; Yu-Tian Wang; Rong Qi; Chun-Hou Zheng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Convolution Neural Networks Using Deep Matrix Factorization for Predicting Circrna-Disease Association. - Zhi-Hao Liu; Cunmei Ji; Jian-Cheng Ni 001; Yu-Tian Wang; Li-Juan Qiao; Chun-Hou Zheng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Potential circRNA-Disease Association Prediction Using DeepWalk and Nonnegative Matrix Factorization. - Li-Juan Qiao; Zhen Gao; Cunmei Ji; Zhi-Hao Liu; Chun-Hou Zheng 001; Yu-Tian Wang (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

scGCC: Graph Contrastive Clustering With Neighborhood Augmentations for scRNA-Seq Data Analysis. - Sheng-Wen Tian; Jiancheng Ni 001; Yu-Tian Wang; Chun-Hou Zheng 001; Cunmei Ji (IEEE J. Biomed. Health Informatics, 2023)

SGLMDA: A Subgraph Learning-Based Method for miRNA-Disease Association Prediction. - Cunmei Ji; Ning Yu; Yu-Tian Wang; Jiancheng Ni 001; Chun-Hou Zheng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

Using Multi-Encoder Semi-Implicit Graph Variational Autoencoder to Analyze Single-Cell RNA Sequencing Data. - Shengwen Tian; Cunmei Ji; Jiancheng Ni 001; Yutian Wang; Chunhou Zheng 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

scAFC: Adaptive Fusion Clustering of Single-Cell RNA-seq Data Through Autoencoder and Graph Attention Networks. - Cunmei Ji; Zhaomei Li; Yutian Wang; Ke Gao; Zongpei Ma; Chunhou Zheng 001 (ICIC (26), 2025)

scMGCC: A Self-supervised Multi-level Graph Contrastive Learning Method for scRNA-seq Data Clustering. - Yutian Wang; Chuanxin Liu; Ke Gao; Cunmei Ji; Chun-Hou Zheng 001 (ICIC (25), 2025)