SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 176–200 of 3304 papers

TitleStatusHype
scMamba: A Pre-Trained Model for Single-Nucleus RNA Sequencing Analysis in Neurodegenerative Disorders—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction NetworksCode0
Learning Effective Dynamics across Spatio-Temporal Scales of Complex Flows—0
A Flag Decomposition for Hierarchical DatasetsCode0
Negative Dependence as a toolbox for machine learning : review and new developments—0
Study on Downlink CSI compression: Are Neural Networks the Only Solution?—0
AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution—0
Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies—0
Geometric Machine Learning on EEG Signals—0
Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach—0
Primary Care Diagnoses as a Reliable Predictor for Orthopedic Surgical Interventions—0
Learning low-dimensional representations of ensemble forecast fields using autoencoder-based methodsCode0
Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds—0
Minimax-Optimal Dimension-Reduced Clustering for High-Dimensional Nonspherical Mixtures—0
Shuttle Between the Instructions and the Parameters of Large Language Models—0
Displacement-Sparse Neural Optimal Transport—0
Physically Interpretable Representation and Controlled Generation for Turbulence Data—0
Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality ReductionCode0
Principal Components for Neural Network InitializationCode0
A Hybrid Data-Driven Approach For Analyzing And Predicting Inpatient Length Of Stay In Health Centre—0
DeepFRC: An End-to-End Deep Learning Model for Functional Registration and ClassificationCode0
RAINER: A Robust Ensemble Learning Grid Search-Tuned Framework for Rainfall Patterns Prediction—0
A Hybrid Deep Learning CNN Model for Enhanced COVID-19 Detection from Computed Tomography (CT) Scan Images—0
Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments—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