SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 341–350 of 3304 papers

TitleStatusHype
TemporalPaD: a reinforcement-learning framework for temporal feature representation and dimension reduction—0
Broadcast Product: Shape-aligned Element-wise Multiplication and Beyond—0
Data-driven Probabilistic Trajectory Learning with High Temporal Resolution in Terminal Airspace—0
Stochastic neighborhood embedding and the gradient flow of relative entropy—0
Exploring Semantic Clustering in Deep Reinforcement Learning for Video Games—0
A parametric framework for kernel-based dynamic mode decomposition using deep learningCode0
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate DataCode0
Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
Representation Loss Minimization with Randomized Selection Strategy for Efficient Environmental Fake Audio Detection—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