SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 501–550 of 3304 papers

TitleStatusHype
Understanding Contrastive Learning via Gaussian Mixture Models—0
You are out of context!—0
XNB: Explainable Class-Specific NaIve-Bayes ClassifierCode0
Detection and tracking of gas plumes in LWIR hyperspectral video sequence data—0
How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?—0
Temporal Streaming Batch Principal Component Analysis for Time Series Classification—0
Golden Ratio-Based Sufficient Dimension Reduction—0
Dimension reduction via score ratio matching—0
Enhancing Graph Attention Neural Network Performance for Marijuana Consumption Classification through Large-scale Augmented Granger Causality (lsAGC) Analysis of Functional MR Images—0
Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data—0
Omics-driven hybrid dynamic modeling of bioprocesses with uncertainty estimation—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
Simultaneous Dimensionality Reduction for Extracting Useful Representations of Large Empirical Multimodal Datasets—0
Enhancing literature review with LLM and NLP methods. Algorithmic trading case—0
Learning Precise, Contact-Rich Manipulation through Uncalibrated Tactile Skins—0
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation—0
Learning signals defined on graphs with optimal transport and Gaussian process regression—0
A Kernelization-Based Approach to Nonparametric Binary Choice Models—0
MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering—0
Unsupervised feature selection algorithm framework based on neighborhood interval disturbance fusion—0
Lossless KV Cache Compression to 2%—0
Efficient Sparse PCA via Block-Diagonalization—0
Approaching Metaheuristic Deep Learning Combos for Automated Data Mining—0
Game Theory Meets Statistical Mechanics in Deep Learning Design—0
Large data limits and scaling laws for tSNE—0
EEG-based 90-Degree Turn Intention Detection for Brain-Computer Interface—0
GleanVec: Accelerating vector search with minimalist nonlinear dimensionality reduction—0
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals—0
TL-PCA: Transfer Learning of Principal Component Analysis—0
Emulators for stellar profiles in binary population modeling—0
Enhancing Affinity Propagation for Improved Public Sentiment InsightsCode0
Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property PredictionCode0
Fast Data-independent KLT Approximations Based on Integer Functions—0
Generalization Ability Analysis of Through-the-Wall Radar Human Activity Recognition—0
Learning Low-Level Causal Relations using a Simulated Robotic ArmCode0
Siamese networks for Poincaré embeddings and the reconstruction of evolutionary trees—0
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility—0
Principal Orthogonal Latent Components Analysis (POLCA Net)Code0
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex—0
Precision Cancer Classification and Biomarker Identification from mRNA Gene Expression via Dimensionality Reduction and Explainable AI—0
Learning Image Derived PDE-Phenotypes from fMRI Data—0
ESPACE: Dimensionality Reduction of Activations for Model Compression—0
Random-projection ensemble dimension reductionCode0
Efficient Large-Scale Urban Parking Prediction: Graph Coarsening Based on Real-Time Parking Service Capability—0
SHAP-CAT: A interpretable multi-modal framework enhancing WSI classification via virtual staining and shapley-value-based multimodal fusion—0
On metric choice in dimension reduction for Fréchet regression—0
Pseudo-Non-Linear Data Augmentation via Energy Minimization—0
A Generalized Mean Approach for Distributed-PCA—0
Knowledge Discovery using Unsupervised Cognition—0
Denoising VAE as an Explainable Feature Reduction and Diagnostic Pipeline for Autism Based on Resting state fMRI—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