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 1241–1250 of 3304 papers

TitleStatusHype
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network—0
Spectrally-Corrected and Regularized Linear Discriminant Analysis for Spiked Covariance Model—0
Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning—0
GENHOP: An Image Generation Method Based on Successive Subspace Learning—0
Probabilistic partition of unity networks for high-dimensional regression problems—0
Detection and Evaluation of Clusters within Sequential Data—0
Enhanced CNN with Global Features for Fault Diagnosis of Complex Chemical Processes—0
Benign AutoencodersCode0
Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval—0
A Unified Framework for Optimization-Based Graph Coarsening—0
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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