SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3101–3110 of 3304 papers

TitleStatusHype
Diffeomorphic brain shape modelling using Gauss-Newton optimisation—0
Diffeomorphic Dimensionality Reduction—0
Differentially private sliced inverse regression in the federated paradigm—0
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm—0
Differential Privacy for Clustering Under Continual Observation—0
Differential Privacy Meets Neural Network Pruning—0
Difficulty in estimating visual information from randomly sampled images—0
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks—0
Diffusion Fingerprints—0
Diffusion map for clustering fMRI spatial maps extracted by independent component analysis—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