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 26–50 of 3304 papers

TitleStatusHype
Autonomous Collaborative Scheduling of Time-dependent UAVs, Workers and Vehicles for Crowdsensing in Disaster Response—0
Quantum Cognition Machine Learning for Forecasting Chromosomal Instability—0
Learning Treatment Representations for Downstream Instrumental Variable Regression—0
Bayesian Data Sketching for Varying Coefficient Regression Models—0
A DNA Methylation Classification Model Predicts Organ and Disease Site—0
Riemannian Principal Component Analysis—0
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures—0
Localizing Persona Representations in LLMs—0
Biological Pathway Guided Gene Selection Through Collaborative Reinforcement LearningCode0
Data-efficient Meta-models for Evaluation of Context-based Questions and Answers in LLMs—0
Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis—0
ALPCAHUS: Subspace Clustering for Heteroscedastic DataCode0
Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems—0
Exponential Convergence of CAVI for Bayesian PCA—0
Fourier-Invertible Neural Encoder (FINE) for Homogeneous Flows—0
NOMAD Projection—0
FlowBERT: Prompt-tuned BERT for variable flow field prediction—0
InstanceBEV: Unifying Instance and BEV Representation for Global Modeling—0
AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal EmbeddingsCode0
A Hybrid Quantum Classical Pipeline for X Ray Based Fracture Diagnosis—0
IISE PG&E Energy Analytics Challenge 2025: Hourly-Binned Regression Models Beat Transformers in Load Forecasting—0
Threshold Strategy for Leaking Corner-Free Hamilton-Jacobi Reachability with Decomposed Computations—0
VizCV: AI-assisted visualization of researchers' publications tracks—0
Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian GeometryCode0
ALPCAH: Subspace Learning for Sample-wise Heteroscedastic DataCode0
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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