Modeling and Analyzing Method for CPS Software Architecture Energy Consumption. - Guangquan Zhang 002; Kan Zhang; Xueyang Zhu; Mingcai Chen; Chengkai Xu; Yuzhen Shao (J. Softw., 2013)

Modeling and Analysis for CPS Physical Entities Based on Spatio-Temporal Petri Net. - Guangquan Zhang 002; Mingtai Zhang; Rongjie Yan; Mingcai Chen; Chengkai Xu; Yejing Li (J. Comput., 2014)

Generation, augmentation, and alignment: A pseudo-source domain based method for source-free domain adaptation. - Yuntao Du 001; Haiyang Yang; Mingcai Chen; Juan Jiang; Hongtao Luo; Chongjun Wang (CoRR, 2021)

Semi-supervised Learning with Multi-Head Co-Training. - Mingcai Chen; Yuntao Du 001; Yi Zhang 073; Shuwei Qian; Chongjun Wang (AAAI, 2022)

CopGAT: Co-propagation Self-supervised Graph Attention Network. - Baoming Zhang; Ming Xu 014; Mingcai Chen; Mingyuan Chen; Chongjun Wang (ISPA/BDCloud/SocialCom/SustainCom, 2022)

Spatial-Temporal Graph Convolutional Gated Recurrent Network for Traffic Forecasting. - Le Zhao; Mingcai Chen; Yuntao Du 001; Haiyang Yang; Chongjun Wang (CoRR, 2022)

Learning with Noisy Labels over Imbalanced Subpopulations. - Mingcai Chen; Yu Zhao 009; Bing He; Zongbo Han; Bingzhe Wu; Jianhua Yao 001 (CoRR, 2022)

Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise. - Mingcai Chen; Hao Cheng 014; Yuntao Du 001; Ming Xu 014; Wenyu Jiang; Chongjun Wang (AAAI, 2023)

READ: Aggregating Reconstruction Error into Out-of-Distribution Detection. - Wenyu Jiang; Yuxin Ge; Hao Cheng 014; Mingcai Chen; Shuai Feng; Chongjun Wang (AAAI, 2023)

LAMB: Label-Induced Mixed-Level Blending for Multimodal Multi-label Emotion Detection. - Shuwei Qian; Ming Guo; Zhicheng Fan; Mingcai Chen; Chongjun Wang (CollaborateCom (2), 2023)

A Flexible Debiasing Framework for Fair Heterogeneous Information Network Embedding. - Meng Cao 004; Mingcai Chen; Jianqing Song; Chen-Xuan Fang; Chongjun Wang (ECAI, 2023)

A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification. - Mingcai Chen; Yu Zhao 009; Zhonghuang Wang; Bing He; Jianhua Yao 001 (IJCAI, 2023)

CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection. - Shuai Feng; Wenyu Jiang; Mingcai Chen; Yuntao Du 001; Hao Cheng 014; Yuxin Ge; Chongjun Wang (SDM, 2023)

LaplaceConfidence: a Graph-based Approach for Learning with Noisy Labels. - Mingcai Chen; Yuntao Du 001; Wei Tang; Baoming Zhang; Hao Cheng 014; Shuwei Qian; Chongjun Wang (CoRR, 2023)

Bidirectional View based Consistency Regularization for Semi-Supervised Domain Adaptation. - Yuntao Du 001; Juan Jiang; Hongtao Luo; Haiyang Yang; Mingcai Chen; Chongjun Wang (Trans. Mach. Learn. Res., 2023)

DOS: Diverse Outlier Sampling for Out-of-Distribution Detection. - Wenyu Jiang; Hao Cheng 014; Mingcai Chen; Chongjun Wang; Hongxin Wei (ICLR, 2024)

V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark. - Yi Xin 003; Siqi Luo; Xuyang Liu; Yuntao Du 001; Haodi Zhou; Xinyu Cheng; Christina E. Lee; Junlong Du; Haozhe Wang 002; Mingcai Chen; Ting Liu; Guimin Hu; et al. (NeurIPS, 2024)

Multi-head co-training: An uncertainty-aware and robust semi-supervised learning framework. - Mingcai Chen; Chongjun Wang (Knowl. Based Syst., 2024)

Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation. - Yuntao Du 001; Haiyang Yang; Mingcai Chen; Hongtao Luo; Juan Jiang; Yi Xin 003; Chongjun Wang (Mach. Learn., 2024)

Robust Logit Adjustment for Learning with Long-Tailed Noisy Data. - Mingcai Chen; Yuntao Du 001; Wenyu Jiang; Baoming Zhang; Shuai Feng; Yi Xin 003; Chongjun Wang (AAAI, 2025)

Normalize Then Propagate: Efficient Homophilous Regularization for Few-Shot Semi-Supervised Node Classification. - Baoming Zhang; Mingcai Chen; Jianqing Song; Shuangjie Li; Jie Zhang; Chongjun Wang (AAAI, 2025)

LaplaceConfidence: A graph-based approach for learning with noisy labels. - Mingcai Chen; Yuntao Du 001; Wei Tang; Baoming Zhang; Chongjun Wang (Intell. Data Anal., 2025)

Multi-source fully test-time adaptation. - Yuntao Du 001; Siqi Luo; Yi Xin 003; Mingcai Chen; Shuai Feng; Mujie Zhang; Chongjun Wang (Neural Networks, 2025)

Learning With Noisy Labels Over Imbalanced Subpopulations. - Mingcai Chen; Yu Zhao 009; Bing He; Zongbo Han; Junzhou Huang; Bingzhe Wu; Jianhua Yao 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models. - Yifan Jia; Kailin Jiang; Yuyang Liang; Qihan Ren; Yi Xin 003; Rui Yang; Fenze Feng; Mingcai Chen; Hengyang Lu; Haozhe Wang 002; Xiaoye Qu; Dongrui Liu; et al. (CoRR, 2025)