SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 361–370 of 3304 papers

TitleStatusHype
A Supervised Tensor Dimension Reduction-Based Prognostics Model for Applications with Incomplete Imaging Data—0
A survey of dimensionality reduction techniques based on random projection—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
A Hybrid Quantum Classical Pipeline for X Ray Based Fracture Diagnosis—0
Approximation of Functions over Manifolds: A Moving Least-Squares Approach—0
A Hybrid Learning Approach to Detecting Regime Switches in Financial Markets—0
A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition—0
Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI—0
A Probabilistic Graph Coupling View of Dimension Reduction—0
Approximation Algorithms for Sparse Principal Component Analysis—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