SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 201210 of 3304 papers

TitleStatusHype
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality ReductionCode1
ProsoBeast Prosody Annotation ToolCode1
A local approach to parameter space reduction for regression and classification tasksCode1
Quantifying Extrinsic Curvature in Neural ManifoldsCode1
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for AutoencodersCode1
Recursive KL Divergence Optimization: A Dynamic Framework for Representation LearningCode1
Rethinking Spatial Dimensions of Vision TransformersCode1
Detection and Retrieval of Out-of-Distribution Objects in Semantic SegmentationCode1
Hartley Spectral Pooling for Deep LearningCode1
Neural Decomposition: Functional ANOVA with Variational AutoencodersCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified