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 891–900 of 3304 papers

TitleStatusHype
Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative ValuesCode0
Manifold learning: what, how, and why—0
Computing Approximate _p Sensitivities—0
Visualizing DNA reaction trajectories with deep graph embedding approachesCode0
ViDa: Visualizing DNA hybridization trajectories with biophysics-informed deep graph embeddingsCode0
Practical considerations for variable screening in the super learnerCode0
3-Dimensional residual neural architecture search for ultrasonic defect detection—0
TailorMe: Self-Supervised Learning of an Anatomically Constrained Volumetric Human Shape Model—0
Learning Collective Behaviors from Observation—0
Language Model Training Paradigms for Clinical Feature EmbeddingsCode0
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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