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 711–720 of 3304 papers

TitleStatusHype
Iterative Cluster Harvesting for Wafer Map Defect Patterns—0
Cross-Temporal Spectrogram Autoencoder (CTSAE): Unsupervised Dimensionality Reduction for Clustering Gravitational Wave GlitchesCode0
Variational Bayesian surrogate modelling with application to robust design optimisation—0
Explainable Light-Weight Deep Learning Pipeline for Improved Drought Stress Identification—0
Formation-Controlled Dimensionality Reduction—0
Quiver Laplacians and Feature SelectionCode0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Variational Bayesian Optimal Experimental Design with Normalizing Flows—0
On Computational Modeling of Sleep-Wake Cycle—0
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference—0
Show:102550
← PrevPage 72 of 331Next →
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