SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 651675 of 3304 papers

TitleStatusHype
Calibrating dimension reduction hyperparameters in the presence of noiseCode0
ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised LearningCode0
Caffe: Convolutional Architecture for Fast Feature EmbeddingCode0
High Dimensional Bayesian Optimization via Supervised Dimension ReductionCode0
Designing Illuminant Spectral Power Distributions for Surface ClassificationCode0
Hillclimb-Causal Inference: A Data-Driven Approach to Identify Causal Pathways Among Parental Behaviors, Genetic Risk, and Externalizing Behaviors in ChildrenCode0
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parametersCode0
Derivative-enhanced Deep Operator NetworkCode0
Detecting Adversarial Examples through Nonlinear Dimensionality ReductionCode0
Computer-aided Interpretable Features for Leaf Image ClassificationCode0
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsCode0
Computer vision-based framework for extracting geological lineaments from optical remote sensing dataCode0
Bubblewrap: Online tiling and real-time flow prediction on neural manifoldsCode0
Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain FeaturesCode0
A comparison of correspondence analysis with PMI-based word embedding methodsCode0
Deep Temporal Clustering: Fully unsupervised learning of time-domain featuresCode0
Degradation Modeling and Prognostic Analysis Under Unknown Failure ModesCode0
Improving text classification with vectors of reduced precisionCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecastingCode0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
Dimension Reduction with Prior Information for Knowledge DiscoveryCode0
A parametric framework for kernel-based dynamic mode decomposition using deep learningCode0
Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinatesCode0
Deep learning to discover and predict dynamics on an inertial manifoldCode0
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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