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 1521–1530 of 3304 papers

TitleStatusHype
Deep Learning for Functional Data Analysis with Adaptive Basis LayersCode1
On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks—0
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in PythonCode1
Topological Indoor Mapping through WiFi Signals—0
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICACode1
Non-PSD Matrix Sketching with Applications to Regression and Optimization—0
Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey—0
ATD: Augmenting CP Tensor Decomposition by Self SupervisionCode1
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery—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