SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 3140 of 3304 papers

TitleStatusHype
Bayesian Optimization of Sampling Densities in MRICode1
BIKED: A Dataset for Computational Bicycle Design with Machine Learning BenchmarksCode1
catch22: CAnonical Time-series CHaracteristicsCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
Autoencoding with a Classifier SystemCode1
Algorithmic Stability and Generalization of an Unsupervised Feature Selection AlgorithmCode1
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breathCode1
ActUp: Analyzing and Consolidating tSNE and UMAPCode1
A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiologyCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified