SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 476500 of 3304 papers

TitleStatusHype
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Differentiable VQ-VAE's for Robust White Matter Streamline EncodingsCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Detecting Adversarial Examples through Nonlinear Dimensionality ReductionCode0
Backprojection for Training Feedforward Neural Networks in the Input and Feature SpacesCode0
A novel approach for Fair Principal Component Analysis based on eigendecompositionCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
Derivative-enhanced Deep Operator NetworkCode0
Learning Low-Level Causal Relations using a Simulated Robotic ArmCode0
Learning Embeddings into Entropic Wasserstein SpacesCode0
Learning sparse codes from compressed representations with biologically plausible local wiring constraintsCode0
Designing Illuminant Spectral Power Distributions for Surface ClassificationCode0
Lens functions for exploring UMAP Projections with Domain KnowledgeCode0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
Effective Dimensionality Reduction for Word EmbeddingsCode0
Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain FeaturesCode0
Bayesian latent structure discovery from multi-neuron recordingsCode0
Deep Symmetric Autoencoders from the Eckart-Young-Schmidt PerspectiveCode0
Deep Temporal Clustering: Fully unsupervised learning of time-domain featuresCode0
Bayesian Non-stationary Linear Bandits for Large-Scale Recommender SystemsCode0
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognitionCode0
Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemiaCode0
Bayesian Non-linear Latent Variable Modeling via Random Fourier FeaturesCode0
DeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI TractographyCode0
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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