high-dimensional-data

Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors

A Python toolbox for gaining geometric insights into high-dimensional data

Vald. A Highly Scalable Distributed Vector Search Engine

Fast Best-Subset Selection Library

A collection of small-sample, high-dimensional microarray data sets to assess machine-learning algorithms and models.

High-dimensional medians (medoid, geometric median, etc.). Fast implementations in Python.

A Framework for Dimensionality Reduction in R

Poisson pseudo-likelihood regression with multiple levels of fixed effects

A general purpose Snakemake workflow and MrBiomics module to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.

A Toolkit for Interactive Statistical Data Visualization

Deep distance-based outlier detection published in KDD18: Learning representations specifically for distance-based outlier detection. Few-shot outlier detection

Implementation of NEWMA: a new method for scalable model-free online change-point detection

🔮 Benchmarking and visualization toolkit for penalized Cox models

A Python package for hubness analysis and high-dimensional data mining

Tree-based visualization for high-dimensional data. Organizes similar items into interactive tree structures for any high-dimensional dataset.

dtour: a tour-de-vis through high-dimensional data

The DPA package is the scikit-learn compatible implementation of the Density Peaks Advanced clustering algorithm. The algorithm provides robust and visual information about the clusters, their statistical reliability and their hierarchical organization.

Statistical quality evaluation of dimensionality reduction algorithms

[SIGMOD 2026] DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search.