SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 1–50 of 3304 papers

TitleStatusHype
Revisiting PCA for time series reduction in temporal dimensionCode7
Dimension Reduction with Locally Adjusted GraphsCode4
XGBoost: A Scalable Tree Boosting SystemCode4
Parametric UMAP embeddings for representation and semi-supervised learningCode3
ivis Dimensionality Reduction Framework for Biomacromolecular SimulationsCode3
Nes2Net: A Lightweight Nested Architecture for Foundation Model Driven Speech Anti-spoofingCode2
Discover and Mitigate Multiple Biased Subgroups in Image ClassifiersCode2
LeanVec: Searching vectors faster by making them fitCode2
High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraftCode2
Modular Boundaries in Recurrent Neural NetworksCode2
Efficient Multi-Scale Attention Module with Cross-Spatial LearningCode2
ImMesh: An Immediate LiDAR Localization and Meshing FrameworkCode2
Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton FormatsCode2
RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language ModelsCode2
A Survey on Generative Diffusion ModelCode2
TTS-GAN: A Transformer-based Time-Series Generative Adversarial NetworkCode2
ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance ComputingCode2
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
Recursive KL Divergence Optimization: A Dynamic Framework for Representation LearningCode1
PhyloProfile v2 -- Exploring multi-layered phylogenetic profiles at scaleCode1
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
Reduced Order Modeling with Shallow Recurrent Decoder NetworksCode1
Stochastic gradient descent estimation of generalized matrix factorization models with application to single-cell RNA sequencing dataCode1
Navigating the Effect of Parametrization for Dimensionality ReductionCode1
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
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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