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Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3076–3100 of 3304 papers

TitleStatusHype
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly DetectionCode0
SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral ImageryCode0
FibeRed: Fiberwise Dimensionality Reduction of Topologically Complex Data with Vector BundlesCode0
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopyCode0
Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental DataCode0
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction NetworksCode0
O(k)-Equivariant Dimensionality Reduction on Stiefel ManifoldsCode0
Super-Resolution Neural OperatorCode0
Auto-Encoding Variational Bayes for Inferring Topics and VisualizationCode0
Learning Neural Representations of Human Cognition across Many fMRI StudiesCode0
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and EmbeddingCode0
Simplicial RegularizationCode0
Estimating a Brain Network Predictive of Stress and Genotype with Supervised AutoencodersCode0
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional RegressionCode0
Autoencoded Image Compression for Secure and Fast TransmissionCode0
Fisher and Kernel Fisher Discriminant Analysis: TutorialCode0
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese NetworksCode0
Fisherposes for Human Action Recognition Using Kinect Sensor DataCode0
Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank EstimationCode0
RaSE: A Variable Screening Framework via Random Subspace EnsemblesCode0
FLeNS: Federated Learning with Enhanced Nesterov-Newton SketchCode0
Throttling Malware Families in 2DCode0
Decentralized State Estimation In A Dimension-Reduced Linear RegressionCode0
Learning sparse codes from compressed representations with biologically plausible local wiring constraintsCode0
Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition ManifoldsCode0
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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