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 381–390 of 3304 papers

TitleStatusHype
Two-Stage Hierarchical and Explainable Feature Selection Framework for Dimensionality Reduction in Sleep Staging—0
Common Steps in Machine Learning Might Hinder The Explainability Aims in Medicine—0
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction AttackCode0
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning—0
Self-Adaptive Quantum Kernel Principal Components Analysis for Compact Readout of Chemiresistive Sensor Arrays—0
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions—0
On latent dynamics learning in nonlinear reduced order modeling—0
PAGE: Parametric Generative Explainer for Graph Neural NetworkCode0
An Embedding is Worth a Thousand Noisy LabelsCode1
ADRS-CNet: An adaptive dimensionality reduction selection and classification network for DNA storage clustering algorithms—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