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 701–725 of 3304 papers

TitleStatusHype
Reduced-Rank Multi-objective Policy Learning and Optimization—0
DIRESA, a distance-preserving nonlinear dimension reduction technique based on regularized autoencoders—0
GARA: A novel approach to Improve Genetic Algorithms' Accuracy and Efficiency by Utilizing Relationships among Genes—0
Dynamical Mode Recognition of Coupled Flame Oscillators by Supervised and Unsupervised Learning Approaches—0
On the Road to Clarity: Exploring Explainable AI for World Models in a Driver Assistance System—0
Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical Systems—0
Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental DataCode0
Contextual Categorization Enhancement through LLMs Latent-Space—0
Machine Learning for Pre/Post Flight UAV Rotor Defect Detection Using Vibration Analysis—0
Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models—0
Cross-Temporal Spectrogram Autoencoder (CTSAE): Unsupervised Dimensionality Reduction for Clustering Gravitational Wave GlitchesCode0
Iterative Cluster Harvesting for Wafer Map Defect Patterns—0
Variational Bayesian surrogate modelling with application to robust design optimisation—0
Explainable Light-Weight Deep Learning Pipeline for Improved Drought Stress Identification—0
Formation-Controlled Dimensionality Reduction—0
Quiver Laplacians and Feature SelectionCode0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
On Computational Modeling of Sleep-Wake Cycle—0
Variational Bayesian Optimal Experimental Design with Normalizing Flows—0
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference—0
Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling—0
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging—0
Human Activity Recognition using Smartphones—0
Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds—0
Preventing Model Collapse in Gaussian Process Latent Variable ModelsCode0
Show:102550
← PrevPage 29 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