Prevent the Language Model from being Overconfident in Neural Machine Translation. - Mengqi Miao; Fandong Meng; Yijin Liu; Xiao-Hua Zhou; Jie Zhou 016 (ACL/IJCNLP (1), 2021)

Adaptive Densely Connected Convolutional Auto-Encoder-Based Feature Learning of Gearbox Vibration Signals. - Mengqi Miao; Changhui Liu; Jianbo Yu (IEEE Trans. Instrum. Meas., 2021)

A Deep Domain Adaptative Network for Remaining Useful Life Prediction of Machines Under Different Working Conditions and Fault Modes. - Mengqi Miao; Jianbo Yu (IEEE Trans. Instrum. Meas., 2021)

Deep sparse representation network for feature learning of vibration signals and its application in gearbox fault diagnosis. - Mengqi Miao; Yuanhang Sun; Jianbo Yu (Knowl. Based Syst., 2022)

A sparse domain adaption network for remaining useful life prediction of rolling bearings under different working conditions. - Mengqi Miao; Jianbo Yu; Zhihong Zhao (Reliab. Eng. Syst. Saf., 2022)

Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis. - Mengqi Miao; Yuanhang Sun; Jianbo Yu (IEEE Trans. Ind. Electron., 2022)

SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems. - Beichuan Zhang 002; Chenggen Sun; Jianchao Tan; Xinjun Cai; Jun Zhao; Mengqi Miao; Kang Yin; Chengru Song; Na Mou; Yang Song 008 (CIKM, 2023)

Selective Domain Adaptation Network for Lithium-ion Battery Health Monitoring. - Mengqi Miao; Jianbo Yu; Pu Yang; Shang Yue; Ruixu Zhou (ICPHM, 2023)

Sparse-Representation-Network-Based Feature Learning of Vibration Signal for Machinery Fault Diagnosis. - Mengqi Miao; Jianbo Yu (IEEE Trans. Ind. Informatics, 2023)

Temporal self-supervised domain adaptation network for machinery fault diagnosis under multiple non-ideal conditions. - Mengqi Miao; Yun Wang; Jianbo Yu (Reliab. Eng. Syst. Saf., 2024)

Deep feature interactive network for machinery fault diagnosis using multi-source heterogeneous data. - Mengqi Miao; Jianbo Yu (Reliab. Eng. Syst. Saf., 2024)