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 126–150 of 3304 papers

TitleStatusHype
Stabilization Analysis and Mode Recognition of Kerosene Supersonic Combustion: A Deep Learning Approach Based on Res-CNN-beta-VAE—0
A Convex formulation for linear discriminant analysis—0
RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning TasksCode0
Cardiomyopathy Diagnosis Model from Endomyocardial Biopsy Specimens: Appropriate Feature Space and Class Boundary in Small Sample Size Data—0
Latent Space Representation of Electricity Market Curves for Improved Prediction Efficiency—0
A Novel Approach for Intrinsic Dimension Estimation—0
Cover Learning for Large-Scale Topology Representation—0
The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality ReductionCode0
Probing Latent Subspaces in LLM for AI Security: Identifying and Manipulating Adversarial States—0
Robust Unsupervised Fault Diagnosis For High-Dimensional Nonlinear Noisy Data—0
Preserving clusters and correlations: a dimensionality reduction method for exceptionally high global structure preservation—0
EigenGS Representation: From Eigenspace to Gaussian Image Space—0
Robust Multilinear Principal Component Analysis—0
DeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI TractographyCode0
Optimal Transport for Brain-Image Alignment: Unveiling Redundancy and Synergy in Neural Information Processing—0
Matrix Factorization for Inferring Associations and Missing Links—0
Low Dimensional Dynamics of Globally Coupled Complex Riccati Equations: Exact Firing-rate Equations for Spiking Neurons with Clustered Substructure—0
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
Label Ranker: Self-Aware Preference for Classification Label Position in Visual Masked Self-Supervised Pre-Trained ModelCode0
Diagnosis of Patients with Viral, Bacterial, and Non-Pneumonia Based on Chest X-Ray Images Using Convolutional Neural Networks—0
Learning Stochastic Dynamical Systems with Structured Noise—0
Inteval Analysis for two spherical functions arising from robust Perspective-n-Lines problem—0
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue OptimizationCode0
Analysis of Evolving Cortical Neuronal Networks Using Visual Informatics—0
Tuning-Free Structured Sparse PCA via Deep Unfolding NetworksCode0
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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