SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 261–270 of 3304 papers

TitleStatusHype
Swin fMRI Transformer Predicts Early Neurodevelopmental Outcomes from Neonatal fMRI—0
Navigating the Effect of Parametrization for Dimensionality ReductionCode1
Circuit design in biology and machine learning. II. Anomaly detection—0
FAST-Splat: Fast, Ambiguity-Free Semantics Transfer in Gaussian Splatting—0
K-means Derived Unsupervised Feature Selection using Improved ADMM—0
Hierarchical Trait-State Model for Decoding Dyadic Social Interactions—0
Dimension Reduction via Sum-of-Squares and Improved Clustering Algorithms for Non-Spherical Mixtures—0
Exploring the Manifold of Neural Networks Using Diffusion Geometry—0
Feature Selection for Network Intrusion Detection—0
Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting—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