SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2451–2460 of 3304 papers

TitleStatusHype
Netboost: Boosting-supported network analysis improves high-dimensional omics prediction in acute myeloid leukemia and Huntington's disease—0
Network Distance Based on Laplacian Flows on Graphs—0
Network Resource Optimization for ML-Based UAV Condition Monitoring with Vibration Analysis—0
Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-perfect Representation Learning—0
Neural dSCA: demixing multimodal interaction among brain areas during naturalistic experiments—0
Neural-Kernelized Conditional Density Estimation—0
Neural method for Explicit Mapping of Quasi-curvature Locally Linear Embedding in image retrieval—0
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture—0
NeurAM: nonlinear dimensionality reduction for uncertainty quantification through neural active manifolds—0
Neuro-mimetic Task-free Unsupervised Online Learning with Continual Self-Organizing Maps—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