SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 101110 of 3304 papers

TitleStatusHype
Application of Clustering Algorithms for Dimensionality Reduction in Infrastructure Resilience Prediction ModelsCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
On Path Integration of Grid Cells: Group Representation and Isotropic ScalingCode1
Explaining dimensionality reduction results using Shapley valuesCode1
Fast and Accurate Network Embeddings via Very Sparse Random ProjectionCode1
Fast conformational clustering of extensive molecular dynamics simulation dataCode1
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spacesCode1
Few-Shot Learning by Dimensionality Reduction in Gradient SpaceCode1
FILP-3D: Enhancing 3D Few-shot Class-incremental Learning with Pre-trained Vision-Language ModelsCode1
A Memory Efficient Baseline for Open Domain Question AnsweringCode1
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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