SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 1071–1080 of 3304 papers

TitleStatusHype
High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction—0
Strategy for Rapid Diabetic Retinopathy Exposure Based on Enhanced Feature Extraction Processing—0
K-SpecPart: Supervised embedding algorithms and cut overlay for improved hypergraph partitioning—0
A Heath-Jarrow-Morton framework for energy markets: a pragmatic approach—0
Wasserstein Dictionaries of Persistence Diagrams—0
The Power of Typed Affine Decision Structures: A Case Study—0
Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability—0
Latent Dynamics Networks (LDNets): learning the intrinsic dynamics of spatio-temporal processes—0
On Manifold Learning in Plato's Cave: Remarks on Manifold Learning and Physical PhenomenaCode0
A Method for Classifying Snow Using Ski-Mounted Strain Sensors—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