SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 911920 of 3304 papers

TitleStatusHype
Gradient-Free Textual Inversion0
Selecting Robust Features for Machine Learning Applications using Multidata Causal DiscoveryCode0
Deep-learning based measurement of planetary radial velocities in the presence of stellar variability0
SELFormer: Molecular Representation Learning via SELFIES Language ModelsCode1
OFTER: An Online Pipeline for Time Series Forecasting0
Multi-Linear Kernel Regression and Imputation in Data Manifolds0
OutCenTR: A novel semi-supervised framework for predicting exploits of vulnerabilities in high-dimensional datasets0
NeuroDAVIS: A neural network model for data visualizationCode0
Maximum Covariance Unfolding Regression: A Novel Covariate-based Manifold Learning Approach for Point Cloud Data0
A Second-Order Majorant Algorithm for Nonnegative Matrix Factorization0
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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