• TISEAN

  • Referenced in 173 articles [sw00967]
  • algorithms for data representation, prediction, noise reduction, dimension and Lyapunov estimation, and nonlinearity testing...
  • UMAP

  • Referenced in 30 articles [sw34900]
  • Uniform Manifold Approximation and Projection for Dimension Reduction. UMAP (Uniform Manifold Approximation and Projection ... novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based ... UMAP has no computational restrictions on embedding dimension, making ... viable as a general purpose dimension reduction technique for machine learning...
  • Leibniz

  • Referenced in 36 articles [sw12871]
  • data estimation by a lazy learner - dimension reduction of models - decomposition of graphs and matrices...
  • Algorithm 913

  • Referenced in 23 articles [sw12775]
  • based on the induced dimension reduction theorem, that provides a way to construct subsequent residuals...
  • VAMPnets

  • Referenced in 19 articles [sw32927]
  • simulated coordinates into structural features, dimension reduction, clustering the dimension-reduced data, and estimation...
  • SADE

  • Referenced in 21 articles [sw07076]
  • ordinary differential equations, order and dimension reductions using Lie symmetries, classification of differential equations, Casimir...
  • HDclassif

  • Referenced in 19 articles [sw11114]
  • model which combines the ideas of dimension reduction and constraints on the model...
  • GAP

  • Referenced in 19 articles [sw26294]
  • effective than conventional graphical methods when dimension reduction techniques fail or when data...
  • dr

  • Referenced in 12 articles [sw14718]
  • package dr: Methods for Dimension Reduction for Regression. Functions, methods, and datasets for fitting dimension ... reduction regression, using slicing (methods SAVE and SIR), Principal Hessian Directions (phd, using residuals ... code for computing permutation tests of dimension. Adding additional methods of estimating dimension is straightforward...
  • BKZ

  • Referenced in 66 articles [sw10242]
  • best lattice reduction algorithm known in practice for high dimension is Schnorr-Euchner...
  • LDR

  • Referenced in 13 articles [sw08893]
  • proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces...
  • Lord-Wingersky

  • Referenced in 13 articles [sw41250]
  • Version 2.0. The 2.0 algorithm utilizes dimension reduction to efficiently compute summed score likelihoods associated...
  • edrGraphicalTools

  • Referenced in 13 articles [sw11105]
  • edrGraphicalTools: Provides tools for dimension reduction methods. This package comes to illustrate the articles ... selecting the number of slices and the dimension of the model in SIR and SAVE...
  • ICtest

  • Referenced in 6 articles [sw36426]
  • Number of Interesting Components in Linear Dimension Reduction. For different linear dimension reduction methods like ... components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number...
  • ldr

  • Referenced in 6 articles [sw16971]
  • package ldr: Methods for likelihood-based dimension reduction in regression. Functions, methods, and data sets ... fitting likelihood-based dimension reduction in regression, using principal fitted components (pfc), likelihood acquired directions...
  • SenticNet

  • Referenced in 14 articles [sw39060]
  • Semantic Web techniques. It uses dimension- ality reduction to infer the polarity of common sense...
  • ePCA

  • Referenced in 8 articles [sw27830]
  • used very generally for dimension reduction and denoising of large data matrices with exponential family ... Marchenko – Pastur law in high dimensions. An open-source implementation is available...
  • WavePacket

  • Referenced in 8 articles [sw19829]
  • focus on open quantum systems and dimension reduction; it also describes the codes for optimal...
  • MAVE

  • Referenced in 5 articles [sw38410]
  • package MAVE: Methods for Dimension Reduction. Functions for dimension reduction, using MAVE (Minimum Average Variance ... kernel version). Methods for selecting the best dimension are also included...
  • clustrd

  • Referenced in 5 articles [sw17529]
  • package clustrd. Methods for Joint Dimension Reduction and Clustering. A class of methods that combine ... dimension reduction and clustering of continuous or categorical data. For continuous data, the package contains...