SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 451500 of 3304 papers

TitleStatusHype
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Auto-Encoding Variational Bayes for Inferring Topics and VisualizationCode0
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG DataCode0
A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies ReconstructionCode0
Introducing user-prescribed constraints in Markov chains for nonlinear dimensionality reductionCode0
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)Code0
Invertible Manifold Learning for Dimension ReductionCode0
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction AttackCode0
Dimension Reduction and MARSCode0
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective OptimizationCode0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Jmp8 at SemEval-2017 Task 2: A simple and general distributional approach to estimate word similarityCode0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
Dimensionality Reduction Meets Message Passing for Graph Node EmbeddingsCode0
Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape ModelsCode0
Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial SystemsCode0
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer ArchitecturesCode0
Label Ranker: Self-Aware Preference for Classification Label Position in Visual Masked Self-Supervised Pre-Trained ModelCode0
Dimensionality Reduction using Similarity-induced EmbeddingsCode0
Autonomous skill discovery with Quality-Diversity and Unsupervised DescriptorsCode0
Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic DischargesCode0
Latent regularization for feature selection using kernel methods in tumor classificationCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in PipesCode0
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