SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 110 of 3304 papers

TitleStatusHype
Revisiting PCA for time series reduction in temporal dimensionCode7
Dimension Reduction with Locally Adjusted GraphsCode4
XGBoost: A Scalable Tree Boosting SystemCode4
ivis Dimensionality Reduction Framework for Biomacromolecular SimulationsCode3
Parametric UMAP embeddings for representation and semi-supervised learningCode3
High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraftCode2
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
ImMesh: An Immediate LiDAR Localization and Meshing FrameworkCode2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
Efficient Multi-Scale Attention Module with Cross-Spatial LearningCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified