Sparse Python Packages

tabmat

Efficient matrix representations for working with tabular data

libraft-cu12

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.

pylibraft-cu12

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.

libcuvs-cu12

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

raft-dask-cu12

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.

torch-sparse

PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

cuvs-cu12

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

libraft-cu13

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.

pylibraft-cu13

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.

libcuvs-cu13

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

python-graphblas

Python library for GraphBLAS: high-performance sparse linear algebra for scalable graph analytics

cooler

A cool place to store your Hi-C

cuvs-cu13

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

scikit-sundae

Python bindings to SUNDIALS differential algebraic equation solvers

sparse-dot-mkl

Python wrapper for Intel Math Kernel Library (MKL) matrix multiplication

genieclust

Genie: Fast and Robust Hierarchical Clustering

pyrregular

Irregular time series in Python: datasets, classifiers and the benchmark from our ICLR 2026 paper.

raft-dask-cu13

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.

libsps

O(1) region count queries using sparse prefix sums

tmu

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.

grblas

Python library for GraphBLAS: high-performance sparse linear algebra for scalable graph analytics

matrepr

Format matrices and tensors to HTML, string, and LaTeX, with Jupyter integration.

mlx-lattice

Sparse convolution library for MLX designed for point cloud operation.

pylibraft-cu11

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.