SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 571–580 of 3304 papers

TitleStatusHype
Shape-informed surrogate models based on signed distance function domain encoding—0
User-friendly Foundation Model Adapters for Multivariate Time Series Classification—0
The Impact of Element Ordering on LM Agent PerformanceCode0
Unlocking NACE Classification Embeddings with OpenAI for Enhanced Analysis and Processing—0
Cost-informed dimensionality reduction for structural digital twin technologies—0
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction—0
HAVANA: Hierarchical stochastic neighbor embedding for Accelerated Video ANnotAtions—0
A clustering adaptive Gaussian process regression method: response patterns based real-time prediction for nonlinear solid mechanics problems—0
Multiview Canonical Correlation Analysis for Automatic Pathological Speech Detection—0
Relevance for Human Robot Collaboration—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