SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1231–1240 of 3304 papers

TitleStatusHype
Deep Amortized Variational Inference for Multivariate Time Series Imputation with Latent Gaussian Process Models—0
Are Latent Factor Regression and Sparse Regression Adequate?—0
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap—0
A Knowledge-based Representation for Cross-Language Document Retrieval and Categorization—0
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification—0
Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images—0
A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis—0
Decoding Imagined Speech and Computer Control using Brain Waves—0
Decoding Emotional Experience through Physiological Signal Processing—0
A Reconfigurable Low Power High Throughput Architecture for Deep Network Training—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