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 1131–1140 of 3304 papers

TitleStatusHype
CASS: Cross Adversarial Source Separation via Autoencoder—0
End-to-end translation of human neural activity to speech with a dual-dual generative adversarial network—0
Building Models for Biopathway Dynamics Using Intrinsic Dimensionality Analysis—0
Enhanced CNN with Global Features for Fault Diagnosis of Complex Chemical Processes—0
Efficient Optimization for Discriminative Latent Class Models—0
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images—0
Estimating covariance and precision matrices along subspaces—0
Enhanced Sampling with Machine Learning: A Review—0
Causal Deep Learning—0
Estimating Model Uncertainty of Neural Network in Sparse Information Form—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