sparse

LibRec: A Leading Java Library for Recommender Systems, see

The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs

A fast, memory efficient hash map for C++

PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

Library for specialized dense and sparse matrix operations, and deep learning primitives.

SPLADE: sparse neural search (SIGIR21, SIGIR22)

Library for faster pinned CPU <-> GPU transfer in Pytorch

Forensics tool for NTFS (parser, mft, bitlocker, deleted files)

cuVS - a library for vector search and clustering on the GPU

A model compression and acceleration toolbox based on pytorch.

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

[NeurIPS 2022, T-PAMI 2023] Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models

The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.

Sparo optimizes performance of Git operations for your large frontend monorepo.

Sparse and structured neural attention mechanisms

A cool place to store your Hi-C

Sparse and Structured Tensor Compiler

P-NET, Biologically informed deep neural network for prostate cancer classification and discovery

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.