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 276–300 of 3304 papers

TitleStatusHype
A Multimodal Intermediate Fusion Network with Manifold Learning for Stress Detection—0
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
Applying a random projection algorithm to optimize machine learning model for breast lesion classification—0
A Multimodal Data-driven Framework for Anxiety Screening—0
A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs—0
A Deep Graph Embedding Network Model for Face Recognition—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Achieving Fair PCA Using Joint Eigenvalue Decomposition—0
3-Dimensional residual neural architecture search for ultrasonic defect detection—0
Applying Graph-based Keyword Extraction to Document Retrieval—0
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
A Deep Convolutional Auto-Encoder with Pooling - Unpooling Layers in Caffe—0
Application of Symmetric Uncertainty and Mutual Information to Dimensionality Reduction and Classification of Hyperspectral Images—0
3D Face Recognition with Sparse Spherical Representations—0
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations—0
Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension—0
Application Research On Real-Time Perception Of Device Performance Status—0
A Method for Classifying Snow Using Ski-Mounted Strain Sensors—0
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction—0
Additive Component Analysis—0
A mechanism-driven reinforcement learning framework for shape optimization of airfoils—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