SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2861–2870 of 3304 papers

TitleStatusHype
Efficient Outlier Removal in Large Scale Global Structure-from-MotionCode0
GP-VAE: Deep Probabilistic Time Series ImputationCode0
Intrinsic statistical separation of subpopulations in heterogeneous collective motion via dimensionality reductionCode0
Selecting Robust Features for Machine Learning Applications using Multidata Causal DiscoveryCode0
Efficient Solution of Portfolio Optimization Problems via Dimension Reduction and SparsificationCode0
Interpretable and Compositional Relation Learning by Joint Training with an AutoencoderCode0
The optimal resolution level of a protein is an emergent property of its structure and dynamicsCode0
Multi-view Data Visualisation via Manifold LearningCode0
Interpretable dimensionality reduction using weighted linear transformationCode0
Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property PredictionCode0
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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