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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 2851–2875 of 3304 papers

TitleStatusHype
Uniform-in-Phase-Space Data Selection with Iterative Normalizing FlowsCode0
Efficiently Visualizing Large GraphsCode0
Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity PricesCode0
Efficient Manifold and Subspace Approximations with SphereletsCode0
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis SystemsCode0
Deep Linear Discriminant AnalysisCode0
The neighborhood lattice for encoding partial correlations in a Hilbert spaceCode0
Interactive Latent Interpolation on MNIST DatasetCode0
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient DescentCode0
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance AnalysisCode0
Efficient Outlier Removal in Large Scale Global Structure-from-MotionCode0
GP-VAE: Deep Probabilistic Time Series ImputationCode0
Intrinsic statistical separation of subpopulations in heterogeneous collective motion via dimensionality reductionCode0
Selecting Robust Features for Machine Learning Applications using Multidata Causal DiscoveryCode0
Efficient Solution of Portfolio Optimization Problems via Dimension Reduction and SparsificationCode0
Interpretable and Compositional Relation Learning by Joint Training with an AutoencoderCode0
The optimal resolution level of a protein is an emergent property of its structure and dynamicsCode0
Multi-view Data Visualisation via Manifold LearningCode0
Interpretable dimensionality reduction using weighted linear transformationCode0
Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property PredictionCode0
Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational AutoencodersCode0
A primer on correlation-based dimension reduction methods for multi-omics analysisCode0
Probabilistic Data Analysis with Probabilistic ProgrammingCode0
Interpretable non-linear dimensionality reduction using gaussian weighted linear transformationCode0
Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative ValuesCode0
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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