SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 931–940 of 3304 papers

TitleStatusHype
Statistical physics, Bayesian inference and neural information processing—0
On the Power of SVD in the Stochastic Block Model—0
Cluster Exploration using Informative Manifold ProjectionsCode0
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Robust Principal Component Analysis using Density Power Divergence—0
Elastic deep autoencoder for text embedding clustering by an improved graph regularization—0
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature—0
Analysing race and sex bias in brain age prediction—0
Metastatic Breast Cancer Prognostication Through Multimodal Integration of Dimensionality Reduction Algorithms and Classification Algorithms—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