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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 726–750 of 3304 papers

TitleStatusHype
Accelerating Vision Transformers Based on Heterogeneous Attention Patterns—0
Multiview Transformer: Rethinking Spatial Information in Hyperspectral Image Classification—0
Hybrid Quantum-Classical Machine Learning for Sentiment Analysis—0
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy—0
A Process for Topic Modelling Via Word Embeddings—0
Demystifying Embedding Spaces using Large Language Models—0
Risk factor aggregation and stress testing—0
Deep learning modelling of manufacturing and build variations on multi-stage axial compressors aerodynamics—0
Simultaneous Dimensionality Reduction: A Data Efficient Approach for Multimodal Representations Learning—0
Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein—0
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization—0
Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses—0
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context LearningCode1
Randomized Dimension Reduction with Statistical Guarantees—0
Subsurface Characterization using Ensemble-based Approaches with Deep Generative ModelsCode0
Latent Dynamic Networked System Identification with High-Dimensional Networked Data—0
Statistical physics, Bayesian inference and neural information processing—0
On the Power of SVD in the Stochastic Block Model—0
Cluster Exploration using Informative Manifold ProjectionsCode0
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Robust Principal Component Analysis using Density Power Divergence—0
Elastic deep autoencoder for text embedding clustering by an improved graph regularization—0
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature—0
Analysing race and sex bias in brain age prediction—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