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
DMT-HI: MOE-based Hyperbolic Interpretable Deep Manifold Transformation for Unspervised Dimensionality ReductionCode1
Interpreting Temporal Graph Neural Networks with Koopman TheoryCode1
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximationsCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
An Embedding is Worth a Thousand Noisy LabelsCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACECode1
From Analog to Digital: Multi-Order Digital Joint Coding-Modulation for Semantic CommunicationCode1
VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantificationCode1
CBMAP: Clustering-based manifold approximation and projection for dimensionality reductionCode1
Distributional Principal AutoencodersCode1
scCDCG: Efficient Deep Structural Clustering for single-cell RNA-seq via Deep Cut-informed Graph EmbeddingCode1
Remote sensing framework for geological mapping via stacked autoencoders and clusteringCode1
Targeted Visualization of the Backbone of Encoder LLMsCode1
Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer CompressionCode1
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
GCN-DevLSTM: Path Development for Skeleton-Based Action RecognitionCode1
Light Curve Classification with DistClassiPy: a new distance-based classifierCode1
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spacesCode1
Linear Recursive Feature Machines provably recover low-rank matricesCode1
FILP-3D: Enhancing 3D Few-shot Class-incremental Learning with Pre-trained Vision-Language ModelsCode1
Symplectic Autoencoders for Model Reduction of Hamiltonian SystemsCode1
Metric Space Magnitude for Evaluating the Diversity of Latent RepresentationsCode1
Learning Arousal-Valence Representation from Categorical Emotion Labels of SpeechCode1
Spectral Clustering of Attributed Multi-relational GraphsCode1
Show:102550
← PrevPage 2 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