SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 10011010 of 3304 papers

TitleStatusHype
A Functional approach for Two Way Dimension Reduction in Time Series0
Causal Deep Learning0
Quantum Machine Learning Applied to the Classification of Diabetes0
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis0
Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton FormatsCode2
Theoretical Guarantees for Sparse Principal Component Analysis based on the Elastic Net0
Topological Data Analysis of Spatial Patterning in Heterogeneous Cell Populations: Clustering and Sorting with Varying Cell-Cell Adhesion0
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight ConditionsCode0
Hybrid Quantum-Classical Generative Adversarial Network for High Resolution Image GenerationCode1
Quantifying Extrinsic Curvature in Neural ManifoldsCode1
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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