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 2976–3000 of 3304 papers

TitleStatusHype
A flexible Bayesian g-formula for causal survival analyses with time-dependent confoundingCode0
Quantized Fisher Discriminant AnalysisCode0
White-Box Diffusion Transformer for single-cell RNA-seq generationCode0
A parametric framework for kernel-based dynamic mode decomposition using deep learningCode0
Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time SeriesCode0
Quantum algorithms for SVD-based data representation and analysisCode0
Quantum Annealing for Robust Principal Component AnalysisCode0
Nonlinear demixed component analysis for neural population data as a low-rank kernel regression problemCode0
Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation ClassificationCode0
ProjectionPathExplorer: Exploring Visual Patterns in Projected Decision-Making PathsCode0
Learning GPLVM with arbitrary kernels using the unscented transformationCode0
The Shape of Attraction in UMAP: Exploring the Embedding Forces in Dimensionality ReductionCode0
Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversionCode0
Large-Scale Evaluation of Topic Models and Dimensionality Reduction Methods for 2D Text SpatializationCode0
Quantum-inspired Interpretable Deep Learning Architecture for Text Sentiment AnalysisCode0
Class-constrained t-SNE: Combining Data Features and Class ProbabilitiesCode0
Visualizing Representations of Adversarially Perturbed InputsCode0
Characterization of Phosphorylated Tau-Microtubule complex with Molecular Dynamics (MD) simulationCode0
Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data AnalysisCode0
S+t-SNE -- Bringing Dimensionality Reduction to Data StreamsCode0
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing DataCode0
Anticancer Peptides Classification using Kernel Sparse Representation ClassifierCode0
Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential EquationsCode0
Unsupervised and Supervised Principal Component Analysis: TutorialCode0
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized AutoencodersCode0
Show:102550
← PrevPage 120 of 133Next →
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