There are 2 repositories under sparse-representations topic.
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
Sparse matrix formats for linear algebra supporting scientific and machine learning applications
A MATLAB library for sparse representation problems
Functional models and algorithms for sparse signal processing
:sparkles: A Python package for sparse representations and dictionary learning, including matching pursuit, K-SVD and applications.
Cognitive Computing with Associative Memory
Lite weight wrapper for the independent implementation of SPLADE++ models for search & retrieval pipelines. Models and Library created by Prithivi Da, For PRs and Collaboration checkout the readme.
This repository contains dictionary learning algorithms
On-the-fly computation of IR basis functions
Dynamic matrix type and algorithms for sparse matrices
Optical Coherence Tomography Retinal Image Reconstruction via Non-local Weighted Sparse Representation
This package contains multiple 3D OCT denoising methods, including our proposed mixed multiscale BM4D (mmBM4D), which is one of the fastest multiscale 3D OCT denoising methods.
TF-Tile: an efficient sparse representation for real-valued data
Compressed Sensing and Sparse Recovery Algorithms and more!
Sparse representation solvers for P0- and P1-problems
Implementation for the paper "Self-Attention Meta-Learner for Continual Learning" in PyTorch.
Hybrid function sparse representation (HFSR) for super resolution
Implementation for the paper "SpaceNet: Make Free Space For Continual Learning" in PyTorch.
Topics in Signal Processing
Clustering and resource allocation using Deterministic Annealing Approach and Orthogonal Non-negative Matrix Factorization O-(NMF)
Various camera models (Full, Weak and Orthographic) are used to convert 3D real world points into 2D image pixel coordinates by simulating a 'virtual camera'
MATLAB implementation of Orthogonal Matching Pursuit to find the sparsest solution to a linear system of equations, via combinatorial search.
Matlab based implementation for doing face recognition using Discriminative KSVD technique.
A fast MATLAB toolbox for N-dimensional sparse arrays.
Julia array type supporting a default value, useful for storing very sparse information in a space efficient manner, the internal design uses "Dict" for storage, thanks to Tamas K. Papp @ https://github.com/tpapp
High performance triangle counting in large sparse graphs
[ICLR 2021] Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
Sparsity enables subcortical source estimation, Krishnaswamy et al, PNAS 2017
An Exact L0-penalized Problem Solver.