GitHub

Sparse Matrices for Machine Learning in Python.md

Sparse matrices are data structures that efficiently store and operate on matrices with mostly zero elements. They are crucial in machine learning for handling large datasets with many zero values, ...
IEEE

Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering

Abstract: Sparse Matrix-Multivector (SpMM) multiplication is a key kernel for deep learning models and scientific computing applications. However, achieving high performance for SpMM on GPUs is ...
GitHub

Suggestion to update tutorial: deprecated pandas2ri.activate() and sparse matrix conversion for SoupX

The SoupX tutorial uses pandas2ri.activate(), which is deprecated in recent versions of rpy2, and attempts to pass scipy.sparse matrices (like adata.X.T) directly ...
IEEE

Sparse Linear Arrays for Direction-of-Arrival Estimation: A Tutorial Overview

Abstract: Sparse linear arrays serve as the fundamental basis for sparse signal processing and have demonstrated remarkable direction-of-arrival (DOA) estimation performance. Due to the merit of ...