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 331–340 of 3304 papers

TitleStatusHype
Global explainability of a deep abstaining classifier—0
Scalable Geometric Learning with Correlation-Based Functional Brain NetworksCode0
Data-Driven Forecasting of High-Dimensional Transient and Stationary Processes via Space-Time Projection—0
Graph Transformer-Based Flood Susceptibility Mapping: Application to the French Riviera and Railway Infrastructure Under Climate Change—0
Solve sparse PCA problem by employing Hamiltonian system and leapfrog method—0
Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data—0
Rerouting Connection: Hybrid Computer Vision Analysis Reveals Visual Similarity Between Indus and Tibetan-Yi Corridor Writing SystemsCode0
Interpretable dimensionality reduction using weighted linear transformationCode0
Model-free Vehicle Rollover Prevention: A Data-driven Predictive Control Approach—0
Tracking the topology of neural manifolds across populationsCode0
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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