Mengqi Miao

According to our database, Mengqi Miao authored at least 11 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Deep feature interactive network for machinery fault diagnosis using multi-source heterogeneous data.

Mengqi Miao, Jianbo Yu

Reliab. Eng. Syst. Saf., February, 2024

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

2023

Sparse-Representation-Network-Based Feature Learning of Vibration Signal for Machinery Fault Diagnosis.

Mengqi Miao, Jianbo Yu

IEEE Trans. Ind. Informatics, May, 2023

Selective Domain Adaptation Network for Lithium-ion Battery Health Monitoring.

Mengqi Miao, Jianbo Yu, Pu Yang, Shang Yue, Ruixu Zhou

Proceedings of the IEEE International Conference on Prognostics and Health Management, 2023

SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems.

Beichuan Zhang, Chenggen Sun, Jianchao Tan, Xinjun Cai, Jun Zhao, Mengqi Miao, Kang Yin, Chengru Song, Na Mou, Yang Song

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

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

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

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

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

Adaptive Densely Connected Convolutional Auto-Encoder-Based Feature Learning of Gearbox Vibration Signals.

Mengqi Miao, Changhui Liu, Jianbo Yu

IEEE Trans. Instrum. Meas., 2021

Prevent the Language Model from being Overconfident in Neural Machine Translation.

Mengqi Miao, Fandong Meng, Yijin Liu, Xiao-Hua Zhou, Jie Zhou

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021