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 1311–1320 of 3304 papers

TitleStatusHype
Cost-informed dimensionality reduction for structural digital twin technologies—0
Cost-efficient Gaussian Tensor Network Embeddings for Tensor-structured Inputs—0
Applying a random projection algorithm to optimize machine learning model for breast lesion classification—0
A Heath-Jarrow-Morton framework for energy markets: a pragmatic approach—0
Accelerated Canonical Polyadic Decomposition by Using Mode Reduction—0
Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems—0
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality—0
CO-SNE: Dimensionality Reduction and Visualization for Hyperbolic Data—0
Cortical spatio-temporal dimensionality reduction for visual grouping—0
Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images—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