SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 311–320 of 3304 papers

TitleStatusHype
InfoClus: Informative Clustering of High-dimensional Data Embeddings—0
Effective dimensionality reduction for Greeks computation using Randomized QMC—0
On relative universality, regression operator, and conditional independence—0
Generalized probabilistic canonical correlation analysis for multi-modal data integration with full or partial observationsCode0
SPreV—0
An Incremental Non-Linear Manifold Approximation Method—0
Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design—0
PCA-RAG: Principal Component Analysis for Efficient Retrieval-Augmented Generation—0
Dimension reduction for derivative-informed operator learning: An analysis of approximation errors—0
Hodge Laplacians and Hodge Diffusion Maps—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