SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 601–650 of 3304 papers

TitleStatusHype
Self-Adaptive Quantum Kernel Principal Components Analysis for Compact Readout of Chemiresistive Sensor Arrays—0
On latent dynamics learning in nonlinear reduced order modeling—0
PAGE: Parametric Generative Explainer for Graph Neural NetworkCode0
ADRS-CNet: An adaptive dimensionality reduction selection and classification network for DNA storage clustering algorithms—0
Robust spectral clustering with rank statistics—0
Quantum-inspired Interpretable Deep Learning Architecture for Text Sentiment AnalysisCode0
OPDR: Order-Preserving Dimension Reduction for Semantic Embedding of Multimodal Scientific Data—0
"Normalized Stress" is Not Normalized: How to Interpret Stress CorrectlyCode0
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling—0
Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines—0
Identifying Feedforward and Feedback Controllable Subspaces of Neural Population Dynamics—0
Towards aerodynamic surrogate modeling based on β-variational autoencodersCode0
NeurAM: nonlinear dimensionality reduction for uncertainty quantification through neural active manifolds—0
Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions—0
Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN—0
Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
On Probabilistic Embeddings in Optimal Dimension Reduction—0
Principal component analysis balancing prediction and approximation accuracy for spatial dataCode0
Feature Clock: High-Dimensional Effects in Two-Dimensional Plots—0
Automated Classification of Dry Bean Varieties Using XGBoost and SVM Models—0
GNUMAP: A Parameter-Free Approach to Unsupervised Dimensionality Reduction via Graph Neural Networks—0
A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text SpatializationsCode0
Low dimensional representation of multi-patient flow cytometry datasets using optimal transport for minimal residual disease detection in leukemiaCode0
On-the-fly spectral unmixing based on Kalman filtering—0
Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems—0
Optimal high-precision shadow estimation—0
Word Embedding Dimension Reduction via Weakly-Supervised Feature SelectionCode0
ModalChorus: Visual Probing and Alignment of Multi-modal Embeddings via Modal Fusion MapCode0
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional RegressionCode0
Spectral Self-supervised Feature Selection—0
Unveiling the Potential of BERTopic for Multilingual Fake News Analysis -- Use Case: Covid-19—0
Physics-Informed Geometric Operators to Support Surrogate, Dimension Reduction and Generative Models for Engineering Design—0
Robust Partial Least Squares Using Low Rank and Sparse Decomposition—0
Automatic Prediction of the Performance of Every Parser—0
Single-Sequence-Based Protein Secondary Structure Prediction using One-Hot and Chemical Encodings of Amino Acids—0
Autoencoded Image Compression for Secure and Fast TransmissionCode0
Adversarial Robustness of VAEs across Intersectional SubgroupsCode0
Statistical Advantages of Oblique Randomized Decision Trees and Forests—0
Message-Relevant Dimension Reduction of Neural Populations—0
Latent Diffusion Model for Generating Ensembles of Climate Simulations—0
Credit Risk Assessment Model for UAE Commercial Banks: A Machine Learning Approach—0
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks—0
Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data—0
Bayesian calibration of stochastic agent based model via random forestCode0
Specific language impairment (SLI) detection pipeline from transcriptions of spontaneous narratives—0
A review of unsupervised learning in astronomy—0
EvolvED: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models—0
Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction—0
Latent diffusion models for parameterization and data assimilation of facies-based geomodels—0
Coupled Input-Output Dimension Reduction: Application to Goal-oriented Bayesian Experimental Design and Global Sensitivity AnalysisCode0
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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