SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 18111820 of 3304 papers

TitleStatusHype
Challenging Euclidean Topological AutoencodersCode0
Causal Feature Selection with Dimension Reduction for Interpretable Text Classification0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images0
Invertible Manifold Learning for Dimension ReductionCode0
Less is more: Faster and better music version identification with embedding distillationCode1
Combination of digital signal processing and assembled predictive models facilitates the rational design of proteins0
Optimal High-order Tensor SVD via Tensor-Train Orthogonal IterationCode0
Parameter Optimization using high-dimensional Bayesian Optimization0
Factorized Discriminant Analysis for Genetic Signatures of Neuronal PhenotypesCode0
Algorithms for Nonnegative Matrix Factorization with the Kullback-Leibler DivergenceCode0
Show:102550
← PrevPage 182 of 331Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified