SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 471–480 of 3304 papers

TitleStatusHype
AutoQML: Automatic Generation and Training of Robust Quantum-Inspired Classifiers by Using Genetic Algorithms on Grayscale Images—0
Auto-weighted Mutli-view Sparse Reconstructive Embedding—0
Approximated and User Steerable tSNE for Progressive Visual Analytics—0
AVIDA: Alternating method for Visualizing and Integrating Data—0
A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction—0
A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration—0
A Wasserstein perspective of Vanilla GANs—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
A witness function based construction of discriminative models using Hermite polynomials—0
Active Learning with TensorBoard Projector—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