SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 201250 of 3304 papers

TitleStatusHype
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spacesCode1
Revisiting Dynamic Convolution via Matrix DecompositionCode1
A local approach to parameter space reduction for regression and classification tasksCode1
R-PointHop: A Green, Accurate, and Unsupervised Point Cloud Registration MethodCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
scCDCG: Efficient Deep Structural Clustering for single-cell RNA-seq via Deep Cut-informed Graph EmbeddingCode1
Curvature-based Feature Selection with Application in Classifying Electronic Health RecordsCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
DartMinHash: Fast Sketching for Weighted SetsCode1
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationCode1
Spectral Clustering of Attributed Multi-relational GraphsCode1
Statistical power for cluster analysisCode1
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition PathsCode1
Deep Dimension Reduction for Supervised Representation LearningCode1
A Memory Efficient Baseline for Open Domain Question AnsweringCode1
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
Targeted Visualization of the Backbone of Encoder LLMsCode1
The chemical space of terpenes: insights from data science and AICode1
Multiscale modeling of inelastic materials with Thermodynamics-based Artificial Neural Networks (TANN)Code1
Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!Code1
TLDR: Twin Learning for Dimensionality ReductionCode1
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation VectorsCode1
Principal Component Analysis in Space FormsCode1
Deep Learning of Individual AestheticsCode1
Transform Once: Efficient Operator Learning in Frequency DomainCode1
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality ReductionCode1
t-viSNE: Interactive Assessment and Interpretation of t-SNE ProjectionsCode1
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentationCode0
DimVis: Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting MachineCode0
Dimension Reduction for Data with Heterogeneous MissingnessCode0
Analysis of Self-Supervised Learning and Dimensionality Reduction Methods in Clustering-Based Active Learning for Speech Emotion RecognitionCode0
Reducing the dimensionality of data using tempered distributionsCode0
Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic DischargesCode0
Dimensionality Reduction using Similarity-induced EmbeddingsCode0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer ArchitecturesCode0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
Dimensionality Reduction Meets Message Passing for Graph Node EmbeddingsCode0
An Algorithm for Out-Of-Distribution Attack to Neural Network EncoderCode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
A Clustering Framework for Residential Electric Demand ProfilesCode0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
Intrinsic statistical separation of subpopulations in heterogeneous collective motion via dimensionality reductionCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Dimension Reduction and MARSCode0
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognitionCode0
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in PipesCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
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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