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 161–170 of 3304 papers

TitleStatusHype
Number Representations in LLMs: A Computational Parallel to Human PerceptionCode0
ML-Driven Approaches to Combat Medicare Fraud: Advances in Class Imbalance Solutions, Feature Engineering, Adaptive Learning, and Business Impact—0
Fréchet Cumulative Covariance Net for Deep Nonlinear Sufficient Dimension Reduction with Random Objects—0
A Supervised Screening and Regularized Factor-Based Method for Time Series Forecasting—0
Network Resource Optimization for ML-Based UAV Condition Monitoring with Vibration Analysis—0
Challenges of Multi-Modal Coreset Selection for Depth PredictionCode0
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
Random Forest Autoencoders for Guided Representation Learning—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