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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 2701–2750 of 3304 papers

TitleStatusHype
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Computer vision-based framework for extracting geological lineaments from optical remote sensing dataCode0
Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty QuantificationCode0
Dimensionality Reduction using Similarity-induced EmbeddingsCode0
Benign AutoencodersCode0
Validating Clustering Frameworks for Electric Load Demand ProfilesCode0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
Computer-aided Interpretable Features for Leaf Image ClassificationCode0
Theano: A Python framework for fast computation of mathematical expressionsCode0
Bayesian Sparse Tucker Models for Dimension Reduction and Tensor CompletionCode0
Minimum Spectral Connectivity Projection PursuitCode0
MISS: Multiclass Interpretable Scoring SystemsCode0
Spectral Flow on the Manifold of SPD Matrices for Multimodal Data ProcessingCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
A ripple in time: a discontinuity in American historyCode0
Adversarially-Trained Nonnegative Matrix FactorizationCode0
Dimension Reduction and MARSCode0
Hyperspectral Image Classification: Artifacts of Dimension Reduction on Hybrid CNNCode0
Unsupervised Metric Learning in Presence of Missing DataCode0
A Flexible Framework for Anomaly Detection via Dimensionality ReductionCode0
Reducing the dimensionality of data using tempered distributionsCode0
Mixtures of Skewed Matrix Variate Bilinear Factor AnalyzersCode0
Dimension Reduction for Data with Heterogeneous MissingnessCode0
VAMPnets: Deep learning of molecular kineticsCode0
Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality MetricsCode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Compressive spectral embedding: sidestepping the SVDCode0
ICA-based Resting-State Networks Obtained on Large Autism fMRI Dataset ABIDECode0
Roweis Discriminant Analysis: A Generalized Subspace Learning MethodCode0
A more globally accurate dimensionality reduction method using tripletsCode0
Are We Using Autoencoders in a Wrong Way?Code0
Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic DischargesCode0
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsCode0
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variabilityCode0
The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?Code0
ModalChorus: Visual Probing and Alignment of Multi-modal Embeddings via Modal Fusion MapCode0
The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty QuantificationCode0
RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning TasksCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
Identifying Selections Operating on HIV-1 Reverse Transcriptase via Uniform Manifold Approximation and ProjectionCode0
DimVis: Interpreting Visual Clusters in Dimensionality Reduction With Explainable Boosting MachineCode0
A comparison of correspondence analysis with PMI-based word embedding methodsCode0
ARES: Locally Adaptive Reconstruction-based Anomaly ScoringCode0
Toward the automated analysis of complex diseases in genome-wide association studies using genetic programmingCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
Safe squeezing for antisparse codingCode0
Illuminating Generalization in Deep Reinforcement Learning through Procedural Level GenerationCode0
Differentiable VQ-VAE's for Robust White Matter Streamline EncodingsCode0
Physics-Informed Representation and Learning: Control and Risk QuantificationCode0
A Comparative Study of Machine Learning Methods for Predicting the Evolution of Brain Connectivity from a Baseline TimepointCode0
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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