SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 30813090 of 3304 papers

TitleStatusHype
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction NetworksCode0
O(k)-Equivariant Dimensionality Reduction on Stiefel ManifoldsCode0
Super-Resolution Neural OperatorCode0
Auto-Encoding Variational Bayes for Inferring Topics and VisualizationCode0
Learning Neural Representations of Human Cognition across Many fMRI StudiesCode0
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and EmbeddingCode0
Simplicial RegularizationCode0
Estimating a Brain Network Predictive of Stress and Genotype with Supervised AutoencodersCode0
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional RegressionCode0
Autoencoded Image Compression for Secure and Fast TransmissionCode0
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Benchmark Results

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