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 1201–1250 of 3304 papers

TitleStatusHype
FRE: A Fast Method For Anomaly Detection And Segmentation—0
InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for ImagesCode0
A Generalized EigenGame with Extensions to Multiview Representation LearningCode0
A Bi-level Nonlinear Eigenvector Algorithm for Wasserstein Discriminant AnalysisCode0
Graceful Forgetting II. Data as a Process—0
Comparing Explanation Methods for Traditional Machine Learning Models Part 2: Quantifying Model Explainability Faithfulness and Improvements with Dimensionality Reduction—0
Data Dimension Reduction makes ML Algorithms efficient—0
Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection—0
Topology of cognitive maps—0
Inverse Kernel DecompositionCode0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Dimension Reduction for Efficient Data-Enabled Predictive Control—0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds—0
Genomics Data Analysis via Spectral Shape and Topology—0
A new filter for dimensionality reduction and classification of hyperspectral images using GLCM features and mutual information—0
A Faster Approach to Spiking Deep Convolutional Neural Networks—0
Gravitational Dimensionality Reduction Using Newtonian Gravity and Einstein's General RelativityCode0
Hybridization of filter and wrapper approaches for the dimensionality reduction and classification of hyperspectral images—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Hyperspectral Images Classification and Dimensionality Reduction using spectral interaction and SVM classifier—0
Supervised classification methods applied to airborne hyperspectral images: Comparative study using mutual information—0
A Novel Filter Approach for Band Selection and Classification of Hyperspectral Remotely Sensed Images Using Normalized Mutual Information and Support Vector Machines—0
A novel information gain-based approach for classification and dimensionality reduction of hyperspectral images—0
A novel filter based on three variables mutual information for dimensionality reduction and classification of hyperspectral images—0
A new band selection approach based on information theory and support vector machine for hyperspectral images reduction and classification—0
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation—0
Hyperspectral images classification and Dimensionality Reduction using Homogeneity feature and mutual information—0
New wrapper method based on normalized mutual information for dimension reduction and classification of hyperspectral images—0
A Novel Approach for Dimensionality Reduction and Classification of Hyperspectral Images based on Normalized Synergy—0
An Algorithm and Heuristic based on Normalized Mutual Information for Dimensionality Reduction and Classification of Hyperspectral images—0
NeuroMapper: In-browser Visualizer for Neural Network TrainingCode0
Face Pyramid Vision TransformerCode0
An Experimental Study of Dimension Reduction Methods on Machine Learning Algorithms with Applications to Psychometrics—0
A Dashboard to Analysis and Synthesis of Dimensionality Reduction Methods in Remote Sensing—0
Transformer-based dimensionality reduction—0
Decentralized State Estimation In A Dimension-Reduced Linear RegressionCode0
A Brief Survey on Representation Learning based Graph Dimensionality Reduction Techniques—0
Pinning control of networks: dimensionality reduction through simultaneous block-diagonalization of matrices—0
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration—0
Efficient NTK using Dimensionality Reduction—0
Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network—0
Spectrally-Corrected and Regularized Linear Discriminant Analysis for Spiked Covariance Model—0
Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning—0
GENHOP: An Image Generation Method Based on Successive Subspace Learning—0
Probabilistic partition of unity networks for high-dimensional regression problems—0
Detection and Evaluation of Clusters within Sequential Data—0
Enhanced CNN with Global Features for Fault Diagnosis of Complex Chemical Processes—0
Benign AutoencodersCode0
Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval—0
A Unified Framework for Optimization-Based Graph Coarsening—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