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Causal inference is a permanent challenge topic in statistics, data science, and many other applied fields. Existing machine learning methods often focus on the correlations in the data and ignore the...
A popular self-normalization (SN) approach in time series analysis uses the variance of a partial sum as a self-normalizer. This is known to be sensitive to irregularities such as persistent autocorre...
Score-based generative modeling (SGM) is a highly successful approach for learning a probability distribution from data and generating further samples, based on learning the score function (gradient o...
We study multi-period inventory control systems in which managers face seasonal demands with unknown distributions and make inventory decisions based on past demand data. It can be shown that a data-d...
The optimal planning of condition-based maintenance strategy based on the degradation process is of great concerned in the past few years. A lifetime delayed degradation process with heterogenous degr...
Solving multi-scale PDEs is difficult in high-dimensional and/or convection-dominant cases. The interacting particle methods (IPM) are shown to outperform solving PDEs directly. Examples include compu...
Consumer expenditures in the United Kingdom account for over 50% of Gross Domestic Product on the expenditure side, yet their impact on economic activity is often Global geometric structures live on m...
With noisy and asynchronous high-frequency data collected for an ultra-large number of assets, we estimate high-dimensional spot volatility matrices satisfying a low-rank plus sparse structure. A loca...
In this talk we discuss inverse optimal control for the case where only the output measurements are available. By considering the inverse problem as an identification problem, the focus of the talk is...
In this talk we discuss inverse optimal control for the case where only the output measurements are available. By considering the inverse problem as an identification problem, the focus of the talk is...
Complex nonlinear interplays of multiple scales give rise to many interesting physical phenomena and pose major difficulties for the computer simulation of multiscale PDE models in areas such as reser...
Multinational enterprises actively participate in global production networks. However, the current global value chain accounting framework fails to consider the emissions originating from the producti...
The rank-tracking probability (RTP) is a useful statistical index for measuring the ``tracking ability'' of longitudinal disease risk factors in biomedical studies. A flexible nonparametric method for...
Urban carsharing services provide flexible, affordable and green mobility options where customers can pick up a car from one station and return it to the same station (round trip) or any other station...
近日,对地观测领域国际重要期刊《Journal of Selected Topics in Applied Earth Observations and Remote Sensing》刊发了中国地质大学计算机学院遥感智能解译团队的研究成果——“Channel-Attention-Based DenseNet Network for Remote Sensing Image Scene Classi...

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