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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 111–120 of 3304 papers

TitleStatusHype
Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data—0
Rerouting Connection: Hybrid Computer Vision Analysis Reveals Visual Similarity Between Indus and Tibetan-Yi Corridor Writing SystemsCode0
Interpretable dimensionality reduction using weighted linear transformationCode0
Tracking the topology of neural manifolds across populationsCode0
Model-free Vehicle Rollover Prevention: A Data-driven Predictive Control Approach—0
3D Structural Phenotype of the Optic Nerve Head at the Intersection of Glaucoma and Myopia - A Key to Improving Glaucoma Diagnosis in Myopic Populations—0
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and EmbeddingCode0
Mapping Hymns and Organizing Concepts in the Rigveda: Quantitatively Connecting the Vedic Suktas—0
Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations—0
CASE -- Condition-Aware Sentence Embeddings for Conditional Semantic Textual Similarity Measurement—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