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 311–320 of 3304 papers

TitleStatusHype
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals—0
Emulators for stellar profiles in binary population modeling—0
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximationsCode1
TL-PCA: Transfer Learning of Principal Component Analysis—0
Enhancing Affinity Propagation for Improved Public Sentiment InsightsCode0
Fast Data-independent KLT Approximations Based on Integer Functions—0
Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property PredictionCode0
Learning Low-Level Causal Relations using a Simulated Robotic ArmCode0
Generalization Ability Analysis of Through-the-Wall Radar Human Activity Recognition—0
Siamese networks for Poincaré embeddings and the reconstruction of evolutionary trees—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