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 641–650 of 3304 papers

TitleStatusHype
Characterization of Phosphorylated Tau-Microtubule complex with Molecular Dynamics (MD) simulationCode0
Unsupervised Learning for Fault Detection of HVAC Systems: An OPTICS -based Approach for Terminal Air Handling Units—0
Language-Assisted 3D Scene Understanding—0
A Powerful Face Preprocessing For Robust Kinship Verification based Tensor Analyses—0
Physics-Informed Representation and Learning: Control and Risk QuantificationCode0
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian TextsCode0
Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation—0
A new method color MS-BSIF Features learning for the robust kinship verification—0
Symplectic Autoencoders for Model Reduction of Hamiltonian SystemsCode1
Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion MapsCode0
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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