Abstract: For the interpretability of deep neural networks (DNNs) in visual-related tasks, existing explanation methods commonly generate a saliency map based on the linear relation between output ...
Abstract: This article proposes a data-driven linear parameter variation model predictive control (DDLPVMPC) method for unknown nonlinear (NL) systems. The approach eliminates reliance on prior ...
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, and its ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback