SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 631–640 of 3304 papers

TitleStatusHype
Unveiling the Potential of BERTopic for Multilingual Fake News Analysis -- Use Case: Covid-19—0
Physics-Informed Geometric Operators to Support Surrogate, Dimension Reduction and Generative Models for Engineering Design—0
Robust Partial Least Squares Using Low Rank and Sparse Decomposition—0
Automatic Prediction of the Performance of Every Parser—0
Single-Sequence-Based Protein Secondary Structure Prediction using One-Hot and Chemical Encodings of Amino Acids—0
Autoencoded Image Compression for Secure and Fast TransmissionCode0
Adversarial Robustness of VAEs across Intersectional SubgroupsCode0
Latent Diffusion Model for Generating Ensembles of Climate Simulations—0
Statistical Advantages of Oblique Randomized Decision Trees and Forests—0
Message-Relevant Dimension Reduction of Neural Populations—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