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 1381–1390 of 3304 papers

TitleStatusHype
Consistent Estimation of Low-Dimensional Latent Structure in High-Dimensional Data—0
GANs and Closures: Micro-Macro Consistency in Multiscale Modeling—0
Agriculture Commodity Arrival Prediction using Remote Sensing Data: Insights and Beyond—0
Gauge-optimal approximate learning for small data classification problems—0
Gaussian Determinantal Processes: a new model for directionality in data—0
Gaussian Image Anomaly Detection with Greedy Eigencomponent Selection—0
Gaussian Mixture Models with Component Means Constrained in Pre-selected Subspaces—0
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity—0
Cone-Constrained Principal Component Analysis—0
Frequency-dependent covariance reveals critical spatio-temporal patterns of synchronized activity in the human brain—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