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Sparse Python Packages

Python packages with the GitHub topic sparse. Sorted by relevance, with stars and monthly downloads.
Quantco
tabmat

Efficient matrix representations for working with tabular data

291K 134 8
rapidsai
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.

194K 1K 232
rapidsai
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.

173K 1K 232
rapidsai
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.

82K 1K 232
rapidsai
libcuvs-cu12

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

67K 752 184
rusty1s
torch-sparse

PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

44K 1K 160
rapidsai
cuvs-cu12

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

35K 752 184
rapidsai
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.

23K 1K 232
rapidsai
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.

23K 1K 232
python-graphblas
python-graphblas

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

18K 155 16
open2c
cooler

A cool place to store your Hi-C

15K 237 60
gagolews
genieclust

Genie: Fast and Robust Hierarchical Clustering

6K 73 12
NatLabRockies
scikit-sundae

Python bindings to SUNDIALS differential algebraic equation solvers

6K 26 9
flatironinstitute
sparse-dot-mkl

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

4K 94 11
cair
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.

3K 169 33
Siegel-Lab
libsps

O(1) region count queries using sparse prefix sums

2K 0 0
rapidsai
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.

2K 1K 232
Santosh-Gupta
speedtorch

Fast Pinned CPU -> GPU transfer

2K 682 40
metagraph-dev
grblas

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

2K 155 16
stephenhky
npdict

A Python dictionary wrapper for numpy arrays

1K 1 0
brdav
fastrvm

[fastrvm] Relevance Vector Machine in Python with a C++ core

914 1 0
alugowski
matrepr

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

900 16 0
rapidsai
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.

875 1K 232
rapidsai
raft-dask-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.

836 1K 232
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