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高级讲师

SMBU

徐晨

作者:    审核:    发布时间:2023-09-13    阅读次数:

Chen XU

Senior Lecturer of Mathematics in the Faculty of Engineering at Shenzhen MSU-BIT University (SMBU).


徐晨

深圳北理莫斯科大学工程系 高级讲师,硕士生导师


Dr. Chen XU is dedicated to applying mathematical statistics, signal processing (including Fourier transform, and wavelet analysis), machine learning, as well as their applications in other fields. His past research topics include stochastic discount factor models, time series analysis, fund research, etc. Now he mainly works on supervised learning algorithms in applied mathematics and analyzing the convergence of reinforcement learning algorithms using probability theory, time series, and topology. He has published several papers as the first or corresponding author in top-tier journals and international conferences.


徐晨博士致力于应用数理统计、信号处理(傅里叶变换、小波分析)、机器学习等方法以及它们在其他领域中的应用。以往研究课题包括随机贴现因子模型、时间序列分析、基金研究等。当前工作主要包括使用概率论、时间序列、拓扑等工具对强化学习算法收敛性进行分析,及监督学习算法在应用数学等领域的应用研究。以第一或通讯作者在中国数学会推荐的T1类期刊中国计算机学会推荐的A会议(CVPR)上发表论文。


Selected papers

1. Chen Xu and Ye Zhang*, Estimating the memory parameter for possibly non-linear and non-Gaussian time series with wavelets (2022), Inverse Problems 38(3), https://doi.org/10.1088/1361-6420/ac48ca

2. Jianxun Yang, Chen Xu*, and Ye Zhang, Reconstruction of the S-Wave Velocity via Mixture Density Networks With a New Rayleigh Wave Dispersion Function (2022), IEEE Transactions on Geoscience and Remote Sensing, 60, https://doi.org/10.1109/TGRS.2022.3169236

3. Chen Xu and Ye Zhang*, Estimating Adsorption Isotherm Parameters in Chromatography via a Virtual Injection Promoting Feed-forward Neural Network (2022), Journal of Inverse and Ill-posed Problems, 30(5), https://doi.org/10.1515/jiip-2020-0121

4. Zhi Gao, Chen Xu*, Feng Li, Yunde Jia, Mehrtash Harandi, Yuwei Wu*, Exploring Data Geometry for Continual Learning, The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023)

5. Elizabeth Ann Housworth, Todd B. Walker*, and Chen Xu, Structural asset pricing theory with wavelets (2019), Quantitative Finance, 19(10), https://doi.org/10.1080/14697688.2019.1594350


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