Inspired by the temporal subspace clustering (TSC) method and low-rank matrix approximation constraint, a new model is proposed termed as temporal plus low-rank subspace clustering (TLRSC) by utilizing both the local and global structural information. On one hand, to solve the drawback that the...
Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions SIAM Rev., 53 (2011) Google Scholar [21] C. Bach, D. Ceglia, L. Song, F. Duddeck Randomized low-rank approximation methods for projection-based model order reduction of large nonlinear dyna...
Differences in receptive fields often indicate different abilities to capture long-range dependencies. Simply fusing low-level information may lead to a decrease in detection accuracy for large and medium-sized people in the image. Our MRF module draws inspiration from the concept of DeepLab39and ach...
An MMD matrix \({\left\{{\mathbf{M}}_{C}\right\}}_{c=1}^{C}\) is then constructed based on class labels, used as the distance measurement for minimizing the difference between conditional distribution, as follows: $$\begin{array}{c}{\left({M}_{c}\right)}_{ij}=\left\{\...
Cluster gene markers were identified using the FindAllMarkers() function and the Wilcoxon Rank Sum test. Intestinal epithelial cells, identified as Epcam-positive cells, were annotated based on canonical features from the literature. AddModuleScore function in Seurat with default parameters was used ...
Extracellular matrix ELISA: Enzyme-linked immunosorbent assay EMT: Epithelial-mesenchymal transition EndMT: Endothelial-to-mesenchymal transition FASL: Fas ligand HE: Hematoxylin-eosin GO: Gene Ontology GzmA: Granzyme A HLA: Human leukocyte antigen HPD: Hyperprogressive disease HuNCG: Humani...
Matrix functions of the form f (A) v, where A is a large symmetric matrix, f is a function, and v not equal 0 is a vector, are commonly approximated by first applying a few, say n, steps of the symmetric Lanczos process to A with the initial vector v in order to determine an ...
Peter A. ChewBrett W. BaderUSUS8290961 Jan 13, 2009 Oct 16, 2012 Sandia Corporation Technique for information retrieval using enhanced latent semantic analysis generating rank approximation matrix by factorizing the weighted morpheme-by-document matrix...
P-values were determined by Wilcoxon rank-sum test (two-sided) and adjusted by Benjamini–Hochberg procedure. FC, fold change. c, Low-dimensional UMAP embeddings of the pixel-wise lipid profiles across different brain serial sections, revealing region-specific lipid distributions across a tissue ...
DL can learn very complex non-linear mapping from a partially filled spectrum map to its full-resolution map, with the DL network trained with simulation data; while the traditional matrix completion (MC) method is used for post-processing the DL output map to keep its low-rank property, ...