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 2201–2210 of 3304 papers

TitleStatusHype
Null Space Analysis for Class-Specific Discriminant Learning—0
A Critical Note on the Evaluation of Clustering Algorithms—0
Zero-Shot Feature Selection via Transferring Supervised Knowledge—0
GridDehazeNet: Attention-Based Multi-Scale Network for Image DehazingCode0
Visualizing the PHATE of Neural NetworksCode0
Improving Channel Charting with Representation-Constrained Autoencoders—0
Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored ProjectionsCode0
Neuroscience-inspired online unsupervised learning algorithms—0
Likelihood Contribution based Multi-scale Architecture for Generative Flows—0
Effective Dimensionality Reduction for Word EmbeddingsCode0
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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