SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2251–2260 of 3304 papers

TitleStatusHype
Learning Clustered Representation for Complex Free Energy Landscapes—0
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers—0
Multi-Frequency Vector Diffusion Maps—0
Constructing Energy-efficient Mixed-precision Neural Networks through Principal Component Analysis for Edge IntelligenceCode0
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission—0
Unsupervised and Supervised Principal Component Analysis: TutorialCode0
Linear and Quadratic Discriminant Analysis: TutorialCode0
A Music Classification Model based on Metric Learning and Feature Extraction from MP3 Audio Files—0
Clustering and Recognition of Spatiotemporal Features through Interpretable Embedding of Sequence to Sequence Recurrent Neural Networks—0
The spiked matrix model with generative priorsCode0
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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