IEEE

A Transformer-Based Industrial Time Series Prediction Model With Multivariate Dynamic Embedding

Abstract: Industrial time series prediction (ITSP) is critical to the predictive maintenance system of modern industry. However, time-varying conditions and complex industrial processes cause the ...
IEEE

Multivariate Time Series Forecasting Using Multiscale Recurrent Networks With Scale Attention and Cross-Scale Guidance

Abstract: Multivariate time series (MTS) forecasting is considered as a challenging task due to complex and nonlinear interdependencies between time steps and series. With the advance of deep learning ...
GitHub

Model-Based Clustering and Variable Selection for Multivariate Count Data

Model-based clustering provides a principled way of developing clustering methods. We develop a new model-based clustering methods for count data. The method combines clustering and variable selection ...
Frontiers

Development and comparison of multivariate diagnostic models for rapidly progressive central precocious puberty in girls: the role of serum osteocalcin

Objectives: To develop a diagnostic prediction model for rapidly progressive central precocious puberty (RP-CPP) and evaluate the contribution of osteocalcin(OC) to the model. Methods: For a total of ...