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 1151–1175 of 3304 papers

TitleStatusHype
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps—0
LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AI—0
Supporting Safety Analysis of Image-processing DNNs through Clustering-based Approaches—0
Master's Thesis: Out-of-distribution Detection with Energy-based ModelsCode0
SparCA: Sparse Compressed Agglomeration for Feature Extraction and Dimensionality ReductionCode0
Automatic Debiased Estimation with Machine Learning-Generated Regressors—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
Capacity Analysis of Vector Symbolic Architectures—0
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression—0
Online Kernel Sliced Inverse Regression—0
Information loss from dimensionality reduction in 5D-Gaussian spectral data—0
Using Topological Data Analysis to classify Encrypted Bits—0
Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection and prediction with tunable sparsity; evaluation on simulated and near-infrared (NIR) dataCode0
DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and CheckingCode0
Segmenting thalamic nuclei from manifold projections of multi-contrast MRI—0
Fair and skill-diverse student group formation via constrained k-way graph partitioning—0
Fair Recommendation by Geometric Interpretation and Analysis of Matrix Factorization—0
Topologically Regularized Data EmbeddingsCode0
Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis—0
EPR-Net: Constructing non-equilibrium potential landscape via a variational force projection formulationCode0
KIDS: kinematics-based (in)activity detection and segmentation in a sleep case study—0
ClusTop: An unsupervised and integrated text clustering and topic extraction framework—0
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction—0
A Functional approach for Two Way Dimension Reduction in Time Series—0
Causal Deep Learning—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