non-negative-matrix-factorization

There are 96 repositories under non-negative-matrix-factorization topic.

  • OCTIS

    MIND-Lab/OCTIS

    OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

    Language:Python73915103107
  • jonaschn/awesome-topic-models

    ✨ Awesome - A curated list of amazing Topic Models (implementations, libraries, and resources)

  • CoGAPS

    FertigLab/CoGAPS

    Bayesian MCMC matrix factorization algorithm

    Language:C++66137817
  • neel-dey/robust-nmf

    Python PyTorch (GPU) and NumPy (CPU)-based port of Févotte and Dobigeon's robust-NMF algorithm appearing in "Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization."

    Language:Python612113
  • ahmadvh/Non-Negative-Matrix-factorization---Implemented-in-python

    This repository provides Python implementations for Non-negative Matrix Factorization (NMF) using the Multiplicative Update (MU) algorithm. Two initialization methods are supported: random initialization and Non-negative Double Singular Value Decomposition (NNDSVD). NMF is a matrix factorization technique used in various fields, including topic mod

    Language:Jupyter Notebook584024
  • rajmic/declipping2020_codes

    Codes and data coming with article "A Survey and an Extensive Evaluation of Popular Audio Declipping Methods", and others closely related

    Language:MATLAB475111
  • eesungkim/NMF-Tensorflow

    Non-negative Matrix Factorization (NMF) Tensorflow Implementation

    Language:Python372016
  • satwik77/libnmf

    Optimization and Regularization variants of Non-negative Matrix Factorization (NMF)

    Language:Python32323
  • welch-lab/pyliger

    Python package for integrating and analyzing multiple single-cell datasets (A Python version of LIGER)

    Language:Jupyter Notebook284195
  • ContextLab/seqnmf

    An algorithm for unsupervised discovery of sequential structure

    Language:Python253115
  • neel-dey/robustNTF

    PyTorch implementation of Robust Non-negative Tensor Factorization appearing in N. Dey, et al., "Robust Non-negative Tensor Factorization, Diffeomorphic Motion Correction and Functional Statistics to Understand Fixation in Fluorescence Microscopy".

    Language:Jupyter Notebook20414
  • poyentung/sigma

    Python code for phase identification and spectrum analysis of energy dispersive x-ray spectroscopy (EDS)

    Language:Jupyter Notebook18214
  • lanl/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.

    Language:Python1471054
  • marcromani/cocktail

    A blind source separation package using non-negative matrix factorization and non-negative ICA

    Language:Python14113
  • PhysiologicAILab/FactorizePhys

    FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing [NeurIPS 2024]

    Language:Python14212
  • bpw1621/streamlit-topic-modeling

    Topic modeling streamlit app.

    Language:Python12244
  • DEIB-GECO/NMTF-DrugRepositioning

    Language:Jupyter Notebook12612
  • SUwonglab/CoupledNMF

    Coupled clustering of single cell genomic data

    Language:Python12321
  • alejandrods/Analysis-of-the-robustness-of-NMF-algorithms

    Analysis of the robustness of non-negative matrix factorization (NMF) techniques: L2-norm, L1-norm, and L2,1-norm

    Language:Jupyter Notebook10202
  • wecarsoniv/beta-divergence-metrics

    PyTorch implementations of the beta divergence loss.

    Language:Python10100
  • aliceagrawal/HM-Recommender-System-App

    Built a collaborative filtering and content-based recommendation/recommender system specific to H&M using the Surprise library and cosine similarity to generate similarity and distance-based recommendations.

    Language:Jupyter Notebook7108
  • maryram/DiffStru

    An official implementation of "Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization"

    Language:Python7100
  • duhaime/nmf

    Non-Negative Matrix Factorization

    Language:Python6301
  • mmahesh/cocain-bpg-matrix-factorization

    New Matrix Factorization Algorithms based on Bregman Proximal Gradient: BPG-MF, CoCaIn BPG-MF, BPG-MF-WB

    Language:Python6304
  • pranayshyamkuwar/NMF-For-Classification-of-Defects-on-Steel-Surface-

    Non-negative matrix factorization is applied for classification of defects on steel surface using CNN

    Language:Python5002
  • THUMNLab/M-NMF

    This is a sample implementation of "Community Preserving Network Embedding" (AAAI 2017).

    Language:MATLAB4401
  • zhangzibin/cu-nmf

    Non-negative Matrix Factorization based on cuda, with sparse matrix as input.

    Language:Cuda4201
  • akhsassoualid/Headline_Recommender

    The project develops an application that suggests to the reader more similar articles to that he already read. It uses the embedding algorithms of headlines to create their own numerical representation, which allows to compute the similarity between headlines and get the most similar ones.

    Language:Python3102
  • arpitamangal/fill-missing-values-of-SST

    Filling in missing values of Sea Surface Temperature

    Language:Python3100
  • lanl/DnMFk

    A C++ framework of Distributed Non-Negative Matrix Factorization implementation to find Latent Dimensionality in Big Data

    Language:C++3403
  • NMTFcoclust

    Saeidhoseinipour/NMTFcoclust

    Co-clustering algorithms can seek homogeneous sub-matrices into a dyadic data matrix, such as a document-word matrix.

    Language:Python3000
  • xianchen2/Topic_Modeling

    Python implementation of Non-negative Matrix Factorization

    Language:Jupyter Notebook3100
  • jennalandy/bayesNMF

    R package implementing Bayesian NMF using various models and prior structures.

    Language:R2201
  • jonperk318/machine-learning-analysis-of-hyperspectral-data

    Using Non-negative Matrix Factorization (NMF) and Variational Autoencoder (VAE) machine learning architectures to analyze spatial and spectral features of hyperspectral cathodoluminescence (CL) spectroscopy images taken from hybrid inorganic-organic perovskite material

    Language:Jupyter Notebook2101
  • michalovadek/nmfbin

    Non-Negative Matrix Factorization for Binary Data

    Language:R2181
  • XavierSpycy/NumPyNMF

    NumPyNMF implements nine different Non-negative Matrix Factorization (NMF) algorithms using NumPy library and compares the robustness of each algorithm to five various types of noise in real-world data applications.

    Language:Python2101