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 2301–2325 of 3304 papers

TitleStatusHype
LSTM Autoencoders for Dialect Analysis—0
Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors—0
Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models—0
Machine-Learned HASDM Model with Uncertainty Quantification—0
Machine Learning and Factor-Based Portfolio Optimization—0
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction—0
Machine Learning-Based Prediction of Key Genes Correlated to the Subretinal Lesion Severity in a Mouse Model of Age-Related Macular Degeneration—0
Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress and Stress-related Mental Disorders: A Scoping Review—0
Machine learning for assessing quality of service in the hospitality sector based on customer reviews—0
Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis—0
Machine learning in APOGEE: Identification of stellar populations through chemical abundances—0
Machine Learning in LiDAR 3D point clouds—0
Machine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space—0
Machine Learning of coarse-grained Molecular Dynamics Force Fields—0
Machine Learning Reveals Composition Dependent Thermal Stability in Halide Perovskites—0
Machine-Learning the Classification of Spacetimes—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
Macroscopic Market Making Games via Multidimensional Decoupling Field—0
Making Laplacians commute—0
Manifold Approximation by Moving Least-Squares Projection (MMLS)—0
Manifold Fitting in Ambient Space—0
Manifold Learning for Personalized and Label-Free Detection of Cardiac Arrhythmias—0
Manifold Learning via Manifold Deflation—0
Manifold learning via quantum dynamics—0
Manifold learning: what, how, and why—0
Show:102550
← PrevPage 93 of 133Next →
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