High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.

We unified some latent block models by proposing a flexible ELBM that is extended to SELBM to address the sparse problem by revealing a diagonal structure from sparse datasets. This leads to obtain more homogeneous co-clusters and therefore produce useful, ready-to-use and easy-to-interpret results.

SparseArrays.jl is a Julia stdlib

Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support

The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University.

Sparse multi-dimensional arrays for the PyData ecosystem

Rust Scientific Libary. ODE and DAE (Runge-Kutta) solvers. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers (MUMPS, UMFPACK). Probability distributions. Tensor calculus.

Fortran library to handle sparse matrices

oj! Algorithms

Pytorch Implementation of the sparse attention from the paper: "Generating Long Sequences with Sparse Transformers"

Kokkos C++ Performance Portability Programming Ecosystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels

Compact Software Suite for Scientific Development - Linear Algebra

DBCSR: Distributed Block Compressed Sparse Row matrix library

Python package to accelerate the sparse matrix multiplication and top-n similarity selection

This code reads a matrix in CO-Ordinate (COO) format and writes the output in Compressed Sparse Row (CSR) format

This code demonstrates the use of machine learning to model the multimodal nature of a single cell. Using machine learning to predict RNA from DNA, that is, using chromatin accessibility data to predict the RNA gene expression and to predict surface protein from RNA, that is, using RNA sequence data to predict surface protein levels in a cell

PyTorch-Based Fast and Efficient Processing for Various Machine Learning Applications with Diverse Sparsity

Sparse vectors.

Structured Matrix Package (LBNL)