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 1001–1025 of 3304 papers

TitleStatusHype
Causal Deep Learning—0
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction—0
Quantum Machine Learning Applied to the Classification of Diabetes—0
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis—0
Theoretical Guarantees for Sparse Principal Component Analysis based on the Elastic Net—0
Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton FormatsCode2
Topological Data Analysis of Spatial Patterning in Heterogeneous Cell Populations: Clustering and Sorting with Varying Cell-Cell Adhesion—0
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight ConditionsCode0
Hybrid Quantum-Classical Generative Adversarial Network for High Resolution Image GenerationCode1
Quantifying Extrinsic Curvature in Neural ManifoldsCode1
UNO-QA: An Unsupervised Anomaly-Aware Framework with Test-Time Clustering for OCTA Image Quality Assessment—0
Anticancer Peptides Classification using Kernel Sparse Representation ClassifierCode0
Prediction of Auto Insurance Risk Based on t-SNE Dimensionality Reduction—0
The Underlying Correlated Dynamics in Neural Training—0
Two-sample test based on Self-Organizing Maps—0
Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs—0
Information retrieval in single cell chromatin analysis using TF-IDF transformation methods—0
SpaceEditing: Integrating Human Knowledge into Deep Neural Networks via Interactive Latent Space Editing—0
Signal enhancement for two-dimensional cryo-EM data processingCode0
Shining light on data: Geometric data analysis through quantum dynamics—0
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking—0
DimenFix: A novel meta-dimensionality reduction method for feature preservation—0
Privacy-Preserving Federated Deep Clustering based on GAN—0
Universal Feature Selection Tool (UniFeat): An Open-Source Tool for Dimensionality ReductionCode0
Spatio-Temporal Crop Aggregation for Video Representation Learning—0
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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