ahmadvh / Non-Negative-Matrix-factorization---Implemented-in-pythonLinks
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 …
☆63Updated last year
Alternatives and similar repositories for Non-Negative-Matrix-factorization---Implemented-in-python
Users that are interested in Non-Negative-Matrix-factorization---Implemented-in-python are comparing it to the libraries listed below
Sorting:
- Roundtrip: density estimation with deep generative neural networks☆63Updated last year
- PyTorch Implementations of a VAE and a beta-VAE.☆60Updated 4 years ago
- Pytorch port for Parametric Umap☆45Updated 2 years ago
- Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Emb…☆248Updated 5 years ago
- A Python package for intrinsic dimension estimation☆94Updated 2 months ago
- ☆54Updated last year
- Resources for Machine Learning Explainability☆86Updated last year
- A spectral method for assessing and combining multiple data visualizations☆50Updated 2 years ago
- Contrastive PCA☆229Updated last month
- ☆31Updated 3 years ago
- ☆121Updated 3 years ago
- A pytorch package for non-negative matrix factorization.☆244Updated last year
- Probabilistic Auto-Encoder☆43Updated 2 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆43Updated 3 years ago
- ☆89Updated 2 years ago
- TARDIS: Topological Algorithms for Robust DIscovery of Singularities☆43Updated 2 years ago
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆39Updated 5 years ago
- Code for "DuETT: Dual Event Time Transformer for Electronic Health Records"☆23Updated 2 years ago
- Causal Variational AutoEncoders☆29Updated 5 years ago
- A python implementation of Maximum Variance Unfolding using CVXPY, Numpy, Scipy, and SK-Learn.☆15Updated 7 years ago
- ☆33Updated 6 months ago
- Hypercomplex Neural Networks with PyTorch☆55Updated 2 years ago
- This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…☆20Updated last year
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆147Updated last month
- My Research Journal covering various topics that interest me. They're mostly scattered notes and resources.☆34Updated 3 years ago
- Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)☆109Updated 3 years ago
- A package for Multiple Kernel Learning in Python☆131Updated 2 years ago
- A toy example of VAE-regression network☆71Updated 5 years ago
- Contrastive neighbor embeddings☆56Updated last week