SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1111–1120 of 3304 papers

TitleStatusHype
Vision Transformers for Action Recognition: A Survey—0
Simple and Powerful Architecture for Inductive Recommendation Using Knowledge Graph Convolutions—0
Dimensionality Reduction using Elastic Measures—0
Risk of Bias in Chest Radiography Deep Learning Foundation ModelsCode1
A Survey on Generative Diffusion ModelCode2
Application of advanced machine learning algorithms for anomaly detection and quantitative prediction in protein A chromatography—0
Learning Canonical Embeddings for Unsupervised Shape Correspondence with Locally Linear Transformations—0
Johnson-Lindenstrauss embeddings for noisy vectors -- taking advantage of the noise—0
Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Inverse Problems—0
Embedding Functional Data: Multidimensional Scaling and Manifold Learning—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