Optimal Design Method of Flexible Excitation System for Improving Power System Stability. - Tiantian Zhang; Liping Cheng; Silin He; Minghao Yu; Chengxiong Mao; Dan Wang 008; Jiancheng Zhang; Bing Han; Zheng Tao (IAS, 2020)

Amplification Method of Lung Nodule Data Based on DCGAN Generation Algorithm. - Minghao Yu; Lei Cai; Liwei Gao; Jingyang Gao (ICPCSEE (1), 2020)

Transient Atomization Modeling and Optimal Design of a Medical Air-Compressing Nebulizer. - Minghao Yu; Rui Wang; Jiafeng Yao; Kai Liu 048; Yuxuan Han (IEEE Access, 2020)

Reservoir hosts prediction for COVID-19 by hybrid transfer learning model. - Yun Yang 003; Jing Guo; Pei Wang 016; Yaowei Wang; Minghao Yu; Xiang Wang; Po Yang 001; Liang Sun (J. Biomed. Informatics, 2021)

Design and Field Application of Flexible Excitation System Damping Controllers. - Tiantian Zhang; Chengxiong Mao; Jiancheng Zhang; Jie Tian; Minghao Yu; Kuayu Wu; Hongtao Xiong; Long Wu; Hongfei Yu (IEEE Trans. Ind. Electron., 2021)

Multi-layer information fusion based on graph convolutional network for knowledge-driven herb recommendation. - Yun Yang 003; Yulong Rao; Minghao Yu; Yan Kang 003 (Neural Networks, 2022)

Tokenomic Model of Friend.Tech Social Platform: A Data-driven Analysis. - Kai Liu; Minghao Yu; Yang Jin; Yue Wang; Jiaqi Yan; Xiao Fan Liu (ICDM (Workshops), 2023)

Reaction-diffusion equation driven topology optimization of high-resolution and feature-rich structures using unstructured meshes. - Hao Li 105; Minghao Yu; Pierre Jolivet; Joe Alexandersen; Tsuguo Kondoh; Tiannan Hu; Kozo Furuta; Kazuhiro Izui; Shinji Nishiwaki (Adv. Eng. Softw., 2023)

A Deep Learning-based Grasp Pose Estimation Approach for Large-Size Deformable Objects in Clutter. - Minghao Yu; Zhuo Li; Zhihao Li; Junjia Liu; Tao Teng; Fei Chen 007 (RO-MAN, 2024)

Instruction-Following Long-Horizon Manipulation by LLM-Empowered Symbolic Planner. - Zhihao Li; Junjia Liu; Zhuo Li; Minghao Yu; Tao Teng; Shunbo Zhou; Miao Li 002; Tin Lun Lam; Fei Chen 007 (ROBIO, 2024)

Human-Humanoid Robots Cross-Embodiment Behavior-Skill Transfer Using Decomposed Adversarial Learning from Demonstration. - Junjia Liu; Zhuo Li; Minghao Yu; Zhipeng Dong; Sylvain Calinon; Darwin G. Caldwell; Fei Chen 007 (CoRR, 2024)

Fusing temporal-frequency information with Contrast Learning on Graph Convolution Network to decoding EEG. - Minghao Yu; Qing He 007; Yuji Wang; Nisuo Du (Biomed. Signal Process. Control., 2025)

Adaptive soft contrastive with mutual information for biological time series representation learning. - Minghao Yu; Qing He 007; Zhihao Yang; Nisuo Du (Expert Syst. Appl., 2025)

HirMTL: Hierarchical Multi-Task Learning for dense scene understanding. - Huilan Luo; Weixia Hu; Yixiao Wei; Jianlong He; Minghao Yu (Neural Networks, 2025)

Human-Humanoid Robots' Cross-Embodiment Behavior-Skill Transfer Using Decomposed Adversarial Learning From Demonstration: HOTU, a Human-Humanoid Robots' Skill Transfer Framework. - Junjia Liu; Zhuo Li; Minghao Yu; Zhipeng Dong; Sylvain Calinon; Darwin G. Caldwell; Fei Chen 007 (IEEE Robotics Autom. Mag., 2025)

TCTR: Text-Guided Contrastive Learning with Token-Level Reconstruction Network for missing modalities in multimodal sentiment analysis. - Zhihao Yang; Qing He 007; Minghao Yu; Nisuo Du; Yijie Lu (Inf. Fusion, 2026)