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 271–280 of 3304 papers

TitleStatusHype
Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear FormsCode0
Towards a Fairer Non-negative Matrix Factorization—0
Expected Information Gain Estimation via Density Approximations: Sample Allocation and Dimension Reduction—0
AstroM^3: A self-supervised multimodal model for astronomy—0
White-Box Diffusion Transformer for single-cell RNA-seq generationCode0
Firm Heterogeneity and Macroeconomic Fluctuations: a Functional VAR model—0
ClusterGraph: a new tool for visualization and compression of multidimensional dataCode0
Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach—0
On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution DataCode0
Theoretically informed selection of latent activation in autoencoder based recommender systems—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