53 Open source projects that are alternatives of or similar to UMAP.jl

Uniform Manifold Approximation and Projection

R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)

A comprehensive dimensional reduction framework to recover the latent topology from high-dimensional data.

Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning" (Sainburg, McInnes, Gentner, 2020).

Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).

A fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.

Parallel Barnes-Hut t-SNE implementation written in Rust.

A computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry and imaging data.

Parallel reduction of boundary matrices for Persistent Homology with CUDA

In this repository, You can find the files which implement dimensionality reduction on the hyperspectral image(Indian Pines) with classification.

Estimate dynamic high-order correlations in multivariate timeseries data

create "Karpathy's style" 2d images out of your image embeddings

ADENINE: A Data ExploratioN PipelINE

Minimum-distortion embedding with PyTorch

Synthetic data sets apt for Topological Data Analysis

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

R pipeline for computing persistent homology in topological data analysis. See https://doi.org/10.21105/joss.00860 for more details.

Single-cell Hierarchical Poisson Factorization

ANTz immersive 3D data visualization engine

TLDR is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self-supervised learning losses

topological data analysis of population-scale microbiomes

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Local Fisher Discriminant Analysis in R

This repository contains R code, with which you can create 3D UMAP and tSNE plots of Seurat analyzed scRNAseq data

A Uniform Manifold Approximation and Projection (UMAP) library for Java, developed by Tag.bio in collaboration with Real Time Genomics.

Ensemble topic modelling with pLSA

Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

BEER: Batch EffEct Remover for single-cell data

Streaming, Memory-Limited, r-truncated SVD Revisited!

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

Uncertainty-aware principal component analysis.

Federated Principal Component Analysis Revisited!

A repository of resources for understanding the concepts of machine learning/deep learning.

Comparison of dimensionality reduction methods

A Python Library for Similarity-based Dimensionality Reduction

A fast and flexible framework for data reduction in R

Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

Easy genetic ancestry predictions in Python

The detection of peaks and valleys in a 1d-vector or 2d-array (image)

🕝 Time-warped principal components analysis (twPCA)

Using Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

A curated list of community detection research papers with implementations.

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

Online feature-extraction and classification algorithm that learns representations of input patterns.

tGPLVM: A Nonparametric, Generative Model for Manifold Learning with scRNA-seq experimental data

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

R package for Distance Metric Learning

A topological data analysis library for Haskell

A library for exploring persistent homology