SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 776800 of 3304 papers

TitleStatusHype
Deep Feature Selection using a Teacher-Student NetworkCode0
PLPCA: Persistent Laplacian Enhanced-PCA for Microarray Data AnalysisCode0
DeepFRC: An End-to-End Deep Learning Model for Functional Registration and ClassificationCode0
Practical Hash Functions for Similarity Estimation and Dimensionality ReductionCode0
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing DataCode0
Deep generative LDACode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Principal Components for Neural Network InitializationCode0
DeepHYDRA: Resource-Efficient Time-Series Anomaly Detection in Dynamically-Configured SystemsCode0
Adversarial Canonical Correlation AnalysisCode0
Principal Orthogonal Latent Components Analysis (POLCA Net)Code0
Differentiable VQ-VAE's for Robust White Matter Streamline EncodingsCode0
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight ConditionsCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Designing Illuminant Spectral Power Distributions for Surface ClassificationCode0
Detecting Adversarial Examples through Nonlinear Dimensionality ReductionCode0
Bi-Sparse Unsupervised Feature SelectionCode0
Biological Pathway Guided Gene Selection Through Collaborative Reinforcement LearningCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
BinGAN: Learning Compact Binary Descriptors with a Regularized GANCode0
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parametersCode0
Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reductionCode0
Quantum algorithms for SVD-based data representation and analysisCode0
Degradation Modeling and Prognostic Analysis Under Unknown Failure ModesCode0
Derivative-enhanced Deep Operator NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified