SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 826–850 of 3304 papers

TitleStatusHype
Deep Variational Sufficient Dimensionality Reduction—0
Classification of Schizophrenia from Functional MRI Using Large-scale Extended Granger Causality—0
An Improvement of PAA on Trend-Based Approximation for Time Series—0
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data—0
A survey of dimensionality reduction techniques based on random projection—0
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
DEMEA: Deep Mesh Autoencoders for Non-Rigidly Deforming Objects—0
Demixed Principal Component Analysis—0
A Survey on Archetypal Analysis—0
Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder—0
Demystifying Embedding Spaces using Large Language Models—0
Classification of high-dimensional data with spiked covariance matrix structure—0
Denoising VAE as an Explainable Feature Reduction and Diagnostic Pipeline for Autism Based on Resting state fMRI—0
Density-based Isometric Mapping—0
Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems—0
Classification of EEG Signals using Genetic Programming for Feature Construction—0
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization—0
Asymptotic Generalization Bound of Fisher's Linear Discriminant Analysis—0
Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning—0
Design of Recognition and Evaluation System for Table Tennis Players' Motor Skills Based on Artificial Intelligence—0
Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study—0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—0
Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio—0
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets—0
A framework for streamlined statistical prediction using topic models—0
Show:102550
← PrevPage 34 of 133Next →
All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified