SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 27712780 of 3304 papers

TitleStatusHype
Linear and Quadratic Discriminant Analysis: TutorialCode0
Positive semi-definite embedding for dimensionality reduction and out-of-sample extensionsCode0
Tracking the topology of neural manifolds across populationsCode0
Distributed Lyapunov Functions for Nonlinear NetworksCode0
Derivative-enhanced Deep Operator NetworkCode0
Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier featuresCode0
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable ModelsCode0
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly DetectionCode0
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder ApproachCode0
Practical considerations for variable screening in the super learnerCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified