There are 2 repositories under sparse topic.
LibRec: A Leading Java Library for Recommender Systems, see
The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs
PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations
Library for faster pinned CPU <-> GPU transfer in Pytorch
Forensics tool for NTFS (parser, mft, bitlocker, deleted files)
A model compression and acceleration toolbox based on pytorch.
Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support
Sparse and structured neural attention mechanisms
P-NET, Biologically informed deep neural network for prostate cancer classification and discovery
Python library for GraphBLAS: high-performance sparse linear algebra for scalable graph analytics
Sparse tensors in Julia and more! Datastructure-driven array programing language.
Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.
Attention-guided CNN for image denoising(Neural Networks,2020)
C++ implementation of sparse matrix using CRS (Compressed Row Storage) format
FFM (Field-Awared Factorization Machine) on Spark
Calling the PARDISO library from Julia
Python wrapper for Intel Math Kernel Library (MKL) matrix multiplication
Next generation library for iterative sparse solvers for ROCm platform
A sparse KLU solver for PyTorch.
General, high performance algebraic multigrid solver
Genie: Fast and Robust Hierarchical Clustering with Noise Point Detection - in Python and R
Source code for "Sparse in Space and Time: Audio-visual Synchronisation with Trainable Selectors." (Spotlight at the BMVC 2022)
Make available to Julia the sparse functionality in MKL
Efficient forward- and reverse-mode sparse Jacobians using Jax