Search Results for "multivariate kernel density estimation"

Embedding Atlas is an open-source tool by Apple that provides scalable, interactive visualizations for large embedding datasets. It enables users to visualize, cross-filter, and search through embeddings alongside rich metadata, all in real time using modern web-based technologies. In addition to the command line tool, Embedding Atlas is also available as a Jupyter widget. Finally, components from Embedding Atlas are also available in an npm package. Order-independent transparency ensuring...

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

Nuklei is a C++ library that implements kernel functions and kernel density estimation for SE(3) data. Nuklei also provides tools for manipulating SE(3) transformations, and for manipulating point clouds.

Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities.

The library implements multivariate kernel density estimates via fast fourier transform from http://www.fftw.org/ The main code is used for constructing jet templates for computing data-driven jet substructure estimate for QCD backgrounds.

A library for fast computation of Gauss transforms in multiple dimensions, using the Improved Fast Gauss Transform and Approximate Nearest Neighbor searching. This library is useful for efficient Kernel Density Estimation (KDE) using a Gaussian kernel.

A fast kernel density estimation based classifier. Uses multi resolution KD trees to significantly reduce the number of calculations needed to perform density estimation.

WebDMAP is a web-based disease mapping and analysis program. WebDMAP allows users to create spatially continuous maps of disease burdens using a adaptive kernel density estimation approach.