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 2031–2040 of 3304 papers

TitleStatusHype
Weighted Fisher Discriminant Analysis in the Input and Feature SpacesCode0
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders—0
Company classification using machine learning—0
A new set of cluster driven composite development indicators—0
Gaze-Sensing LEDs for Head Mounted Displays—0
Coupled Control Systems: Periodic Orbit Generation with Application to Quadrupedal Locomotion—0
Unsupervised machine learning of quantum phase transitions using diffusion maps—0
Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters—0
Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO—0
Multivariate Functional Regression via Nested Reduced-Rank Regularization—0
Show:102550
← PrevPage 204 of 331Next →
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