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 1101–1110 of 3304 papers

TitleStatusHype
involve-MI: Informative Planning with High-Dimensional Non-Parametric Beliefs—0
Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth—0
Non-Negative Matrix Factorization with Scale Data Structure Preservation—0
Algorithm-Agnostic Interpretations for Clustering—0
Rethinking Dimensionality Reduction in Grid-based 3D Object Detection—0
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification—0
Game-theoretic Objective Space PlanningCode0
FRANS: Automatic Feature Extraction for Time Series Forecasting—0
Bayesian Optimization of Sampling Densities in MRICode1
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMsCode0
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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