SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 1421–1430 of 3304 papers

TitleStatusHype
GenURL: A General Framework for Unsupervised Representation Learning—0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds—0
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees—0
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease—0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Geometric Machine Learning on EEG Signals—0
Geometry and dimensionality reduction of feature spaces in primary visual cortex—0
Geometry-Aware Hamiltonian Variational Auto-Encoder—0
Geometry of Deep Learning for Magnetic Resonance Fingerprinting—0
Efficient Large-Scale Urban Parking Prediction: Graph Coarsening Based on Real-Time Parking Service Capability—0
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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