SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 26812690 of 3304 papers

TitleStatusHype
Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network0
DPCA: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets0
Bayesian Inference over the Stiefel Manifold via the Givens Representation0
SMSSVD - SubMatrix Selection Singular Value DecompositionCode0
Deep Triphone Embedding Improves Phoneme Recognition0
Elliptical modeling and pattern analysis for perturbation models and classfication0
Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings0
S-Isomap++: Multi Manifold Learning from Streaming Data0
Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model0
Fair Kernel Learning0
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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