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 3291–3300 of 3304 papers

TitleStatusHype
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity—0
Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method—0
Bayesian Exponential Family PCA—0
Dimensionality Reduction for Data in Multiple Feature Representations—0
Diffeomorphic Dimensionality Reduction—0
Supervised Exponential Family Principal Component Analysis via Convex Optimization—0
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification—0
Visualizing Data using t-SNE—0
3D Face Recognition with Sparse Spherical Representations—0
Locality and low-dimensions in the prediction of natural experience from fMRI—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