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 ...

This important study presents single-unit activity collected during model-based (MB) and model-free (MF) reinforcement learning in non-human primates. The dataset was carefully collected, and the ...

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

To overcome these issues, this work proposes an effective two-stage center-symmetry representation-based high-quality localization ... It solves the inconsistency between classification confidence and ...

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

This repository provides python scripts to run community detection on a sptial correlation graph. Further documentation can be found in the following paper: Chen, Y., and Baker, J. W. (2021).

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 ...

5 Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital, Singapore 6 Department of Diagnostic Radiology, Singapore General Hospital, Singapore 7 Department of Nuclear ...