SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1031–1040 of 3304 papers

TitleStatusHype
Autoencoder Enhanced Realised GARCH on Volatility Forecasting—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
Dimensionality Reduction Ensembles—0
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification—0
Dimensionality reduction based on Distance Preservation to Local Mean (DPLM) for SPD matrices and its application in BCI—0
Dimensionality Reduction as Probabilistic Inference—0
Auto-Detection of Safety Issues in Baby Products—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Achieving Fair PCA Using Joint Eigenvalue Decomposition—0
3-Dimensional residual neural architecture search for ultrasonic defect detection—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