t-elf
Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.
rsparse
Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
https://github.com/cbg-ethz/scdef
Deep exponential families for single-cell data.
recometrics
(Python, R, C++) Library-agnostic evaluation framework for implicit-feedback recommender systems
https://github.com/briochemc/hyperdualmatrixtools.jl
A little Julia module to allow factorization and backslash to work with hyperdual-valued arrays and sparse arrays.
https://github.com/conradsnicta/armadillo-code
Armadillo: fast C++ library for linear algebra & scientific computing - https://arma.sourceforge.net
https://github.com/berenslab/rfest
A Python 3 toolbox for neural receptive field estimation using splines and Gaussian priors.
predicting-missing-pairwise-preferences-in-gdm
Predicting missing pairwise preferences from similarity features in group decision making and group recommendation system
suitesparse
SuiteSparse: a suite of sparse matrix packages by @DrTimothyAldenDavis et al. with native CMake support