The Data Matrix:If the data objects in a collection of data all have the same fixed set of numeric attributes, then the data objects can be thought of as points (vectors)in a multidimensional space, where each dimension represents a distinct attribute describing the object. A set of suc...
cudssMatrix_t¶ The structure is a lightweight wrapper around standard dense/sparse matrix parameters and does not own any data arrays. Matrix objects are used to pass matrix of the linear system, as well as solution and right-hand side (even if these are in fact vectors). Currently, cu...
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Three arrays describe the sparse matrix M as follows: The array values contains non-zero elements of the matrix row-by-row. The j-th element of the array columns encodes the column index in the matrix M for the j-th element of the array values. ...
Recent, rapid advances in deep generative models for protein design have focused on small proteins with lots of data. Such models perform poorly on large proteins with limited natural sequences, for instance, the capsid protein of adenoviruses and adeno-
Single-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unify...
common for data engineers to create new datafeaturesfor AI systems to train on. Examples include calculating the average, median, minimum or maximum values, or ratios between values. Many data sets have numerous missing values or sparse data. Column stores perform exceptionally well in such ...
Biodiverse - A tool for the spatial analysis of diversity using indices based on taxonomic, phylogenetic, trait and matrix-based relationships, as well as related environmental and temporal variations. ENMTML - An R package for an integrated construction of Ecological Niche Models. diversitree - In...
sparse data lead to some analytical challenges. While many computational methods have been successfully proposed for analyzing scRNA-seq data, there are still some open problems in this research area. One of the main challenges is the sparsity of the data and the curse of dimensionality present ...
There was a difference in the number of data classes used for training and testing. Accordingly, the final macro F1 score of the proposed model was 0.74; however, the weighted F1 score, considering the difference in the number of data classes, was 0.78. Figure 1 Confusion matrix for the ...