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 451–500 of 3304 papers

TitleStatusHype
Noisy Data Visualization using Functional Data Analysis—0
The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty QuantificationCode0
Deep Reinforcement Learning Behavioral Mode Switching Using Optimal Control Based on a Latent Space Objective—0
Random Subspace Local Projections—0
VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantificationCode1
A comparison of correspondence analysis with PMI-based word embedding methodsCode0
Estimates on the domain of validity for Lyapunov-Schmidt reduction—0
On the Connection Between Non-negative Matrix Factorization and Latent Dirichlet Allocation—0
Performance Examination of Symbolic Aggregate Approximation in IoT Applications—0
Enhancing Sufficient Dimension Reduction via Hellinger CorrelationCode0
Low-dimensional approximations of the conditional law of Volterra processes: a non-positive curvature approach—0
NUTS, NARS, and Speech—0
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE—0
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances—0
Canonical Variates in Wasserstein Metric Space—0
Embedding Compression for Efficient Re-Identification—0
A Survey on Design-space Dimensionality Reduction Methods for Shape Optimization—0
Rank Reduction Autoencoders—0
A Uniform Concentration Inequality for Kernel-Based Two-Sample Statistics—0
Bayesian Inverse Problems with Conditional Sinkhorn Generative Adversarial Networks in Least Volume Latent Spaces—0
Input Guided Multiple Deconstruction Single Reconstruction neural network models for Matrix Factorization—0
Automated Anomaly Detection on European XFEL Klystrons—0
Dual-band feature selection for maturity classification of specialty crops by hyperspectral imaging—0
An Autoencoder and Generative Adversarial Networks Approach for Multi-Omics Data Imbalanced Class Handling and Classification—0
Deep Learning in Earthquake Engineering: A Comprehensive Review—0
Lens functions for exploring UMAP Projections with Domain KnowledgeCode0
Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction—0
Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-perfect Representation Learning—0
DeepHYDRA: Resource-Efficient Time-Series Anomaly Detection in Dynamically-Configured SystemsCode0
Sensitivity Analysis for Active Sampling, with Applications to the Simulation of Analog Circuits—0
Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables—0
Generative adversarial learning with optimal input dimension and its adaptive generator architecture—0
Scalable Amortized GPLVMs for Single Cell Transcriptomics Data—0
Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey—0
GAD: A Real-time Gait Anomaly Detection System with Online Adaptive Learning—0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
TIPAA-SSL: Text Independent Phone-to-Audio Alignment based on Self-Supervised Learning and Knowledge Transfer—0
Out-of-distribution detection based on subspace projection of high-dimensional features output by the last convolutional layerCode0
QUACK: Quantum Aligned Centroid KernelCode0
Utilizing Machine Learning and 3D Neuroimaging to Predict Hearing Loss: A Comparative Analysis of Dimensionality Reduction and Regression Techniques—0
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
CBMAP: Clustering-based manifold approximation and projection for dimensionality reductionCode1
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-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models—0
Show:102550
← PrevPage 10 of 67Next →
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