no code implementations • 2 Jan 2024 • Junliang Wang, Qinghua Zhang, Guanhua Zhu, Guoxi Sun
Our findings demonstrate that the CVGAN model, in terms of both MMD and FID metrics, outperforms many advanced methods in both autoregressive and non-autoregressive generation modes.
no code implementations • 26 Nov 2023 • Junliang Wang, Qinghua Zhang, Guanhua Zhu, Guoxi Sun
Accurate prediction of the Remaining Useful Life (RUL) of rolling bearings is crucial in industrial production, yet existing models often struggle with limited generalization capabilities due to their inability to fully process all vibration signal patterns.
no code implementations • 17 Nov 2023 • Junliang Wang, Qinghua Zhang, Guanhua Zhu, Guoxi Sun
The prediction of the remaining useful life (RUL) of rolling bearings is a pivotal issue in industrial production.
no code implementations • 3 Nov 2023 • Zheyuan Bai, Xinduo Liu, Hailin Hu, Tianyu Guo, Qinghua Zhang, Yunhe Wang
Data-Free Knowledge Distillation (DFKD) plays a vital role in compressing the model when original training data is unavailable.
3 code implementations • 29 May 2023 • Yuchuan Tian, Hanting Chen, Xutao Wang, Zheyuan Bai, Qinghua Zhang, Ruifeng Li, Chao Xu, Yunhe Wang
Recent releases of Large Language Models (LLMs), e. g. ChatGPT, are astonishing at generating human-like texts, but they may impact the authenticity of texts.
no code implementations • 29 May 2023 • Qin Xie, Qinghua Zhang, Shuyin Xia, Fan Zhao, Chengying Wu, Guoyin Wang, Weiping Ding
Second, considering the influence of the sample size within the GB on the GB's quality, based on the GBG++ method, an improved GB-based $k$-nearest neighbors algorithm (GB$k$NN++) is presented, which can reduce misclassification at the class boundary.