The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...

We propose a novel unified spatial–temporal regression framework named Generalized Spatial–Temporal Regression Graph Convolutional Transformer ... improved GCN and Transformer Encoder to learn ...

This project implements a linear regression model to predict the number of crew members required for cruise ships, based on various ship characteristics. This exercise is part of the course "Spark and ...

Abstract: Multiview representation learning techniques based on deep correlation maximization have become increasingly popular for learning meaningful and compact representations from multiview data.

The results of Random Forest regression, XGBoost regression and Gradient-enhanced ... Where ‖W‖ is the parametrization of the hyperplane and the constant b is the intercept in the linear equation. In ...

Multivariate logistic regression was used for the prediction of binarized mRS 90, and model comparison was conducted using chi-squared tests. Multivariate linear regression was used for the prediction ...