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 1761–1770 of 3304 papers

TitleStatusHype
Exploring Predictive States via Cantor Embeddings and Wasserstein Distance—0
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games—0
Exploring the Deep Feature Space of a Cell Classification Neural Network—0
Exploring the Limits of KV Cache Compression in Visual Autoregressive Transformers—0
Exploring the Manifold of Neural Networks Using Diffusion Geometry—0
Exploring the Unfairness of DP-SGD Across Settings—0
Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation—0
Exponential Convergence of CAVI for Bayesian PCA—0
Exponential Family Embeddings—0
Expressing Facial Structure and Appearance Information in Frequency Domain for Face Recognition—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