SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2361–2370 of 3304 papers

TitleStatusHype
Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra—0
Unsupervised machine learning of quantum phase transitions using diffusion maps—0
Unsupervised model compression for multilayer bootstrap networks—0
Unsupervised Non Linear Dimensionality Reduction Machine Learning methods applied to Multiparametric MRI in cerebral ischemia: Preliminary Results—0
Unsupervised outlier detection to improve bird audio dataset labels—0
Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis—0
Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank—0
Unsupervised vehicle recognition using incremental reseeding of acoustic signatures—0
Unveiling the Potential of BERTopic for Multilingual Fake News Analysis -- Use Case: Covid-19—0
Updating Rare Term Vector Replacement—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