SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 8190 of 3304 papers

TitleStatusHype
IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimationCode1
HEFT: Homomorphically Encrypted Fusion of Biometric TemplatesCode1
Towards a More Rigorous Science of Blindspot Discovery in Image Classification ModelsCode1
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition PathsCode1
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative LearningCode1
GiDR-DUN; Gradient Dimensionality Reduction -- Differences and UnificationCode1
Few-Shot Learning by Dimensionality Reduction in Gradient SpaceCode1
SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time SeriesCode1
Trainable Weight Averaging: A General Approach for Subspace TrainingCode1
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series ForecastingCode1
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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