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Dimensionality Reduction

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

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Papers

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Showing 951–1000 of 3304 papers

TitleStatusHype
Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning—0
Automatic Debiased Estimation with Machine Learning-Generated Regressors—0
Dimension reduction and redundancy removal through successive Schmidt decompositions—0
Stochastic neighborhood embedding and the gradient flow of relative entropy—0
Clustering and Recognition of Spatiotemporal Features through Interpretable Embedding of Sequence to Sequence Recurrent Neural Networks—0
Dimensionality Reduction of Collective Motion by Principal Manifolds—0
Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis—0
Dimensionality Reduction of Affine Variational Inequalities Using Random Projections—0
Dimension reduction for derivative-informed operator learning: An analysis of approximation errors—0
Dimension Reduction for Efficient Data-Enabled Predictive Control—0
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference—0
A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model—0
Dimensionality reduction methods for molecular simulations—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Automatic dimensionality reduction of Twin-in-the-Loop Observers—0
Dimension reduction in recurrent networks by canonicalization—0
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification—0
Dimensionality Reduction in Deep Learning for Chest X-Ray Analysis of Lung Cancer—0
Dimension reduction of open-high-low-close data in candlestick chart based on pseudo-PCA—0
Dimension Reduction Using Active Manifolds—0
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds—0
Dimension reduction via score ratio matching—0
Dimension Reduction via Sum-of-Squares and Improved Clustering Algorithms for Non-Spherical Mixtures—0
Automatic Collection Creation and Recommendation—0
Dimensionality Reduction for Wasserstein Barycenter—0
Dimensionality Reduction for Tukey Regression—0
Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis—0
Direct Estimation of the Derivative of Quadratic Mutual Information with Application in Supervised Dimension Reduction—0
Direction and Constraint in Phenotypic Evolution: Dimension Reduction and Global Proportionality in Phenotype Fluctuation and Responses—0
Automated Disease Normalization with Low Rank Approximations—0
DIRESA, a distance-preserving nonlinear dimension reduction technique based on regularized autoencoders—0
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification—0
A Multimodal Intermediate Fusion Network with Manifold Learning for Stress Detection—0
Dimensionality reduction for time series data—0
Discovering Interpretable Machine Learning Models in Parallel Coordinates—0
Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization—0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Discovery of sustainable energy materials via the machine-learned material space—0
Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication—0
Discriminative convolutional Fisher vector network for action recognition—0
Dimensionality Reduction for Sentiment Classification: Evolving for the Most Prominent and Separable Features—0
Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI—0
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models—0
Advancing the dimensionality reduction of speaker embeddings for speaker diarisation: disentangling noise and informing speech activity—0
Automated Anomaly Detection on European XFEL Klystrons—0
Disentangling Generative Factors of Physical Fields Using Variational Autoencoders—0
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography—0
Disentangling stellar atmospheric parameters in astronomical spectra using Generative Adversarial Neural Networks—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
A Class-Based Agreement Model for Generating Accurately Inflected Translations—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