SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 391–400 of 3304 papers

TitleStatusHype
Disentangled Latent Spaces for Reduced Order Models using Deterministic Autoencoders—0
A Neural Operator-Based Emulator for Regional Shallow Water Dynamics—0
Reverse Markov Learning: Multi-Step Generative Models for Complex Distributions—0
Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic DischargesCode0
Random Forest Autoencoders for Guided Representation Learning—0
BOLIMES: Boruta and LIME optiMized fEature Selection for Gene Expression Classification—0
Lifespan tree of brain anatomy: diagnostic values for motor and cognitive neurodegenerative diseases—0
Data-Enabled Predictive Control for Flexible Spacecraft—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
scMamba: A Pre-Trained Model for Single-Nucleus RNA Sequencing Analysis in Neurodegenerative Disorders—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