SOTAVerified

Imputation

Substituting missing data with values according to some criteria.

Papers

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Showing 901–950 of 1237 papers

TitleStatusHype
Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation—0
ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals—0
tsrobprep - an R package for robust preprocessing of time series data—0
Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data—0
Multi-objective Feature Selection with Missing Data in Classification—0
Recursive input and state estimation: A general framework for learning from time series with missing data—0
Avoiding bias when inferring race using name-based approaches—0
An Update to the Minho Quotation Resource—0
Contextual HyperNetworks for Novel Feature Adaptation—0
Simple Imputation Rules for Prediction with Missing Data: Contrasting Theoretical Guarantees with Empirical Performance—0
Variable selection with missing data in both covariates and outcomes: Imputation and machine learningCode0
Fast model-based clustering of partial recordsCode0
Handling Missing Observations with an RNN-based Prediction-Update Cycle—0
Simulation comparisons between Bayesian and de-biased estimators in low-rank matrix completionCode0
Deep Distribution-preserving Incomplete Clustering with Optimal Transport—0
VEXAS: VISTA EXtension to Auxiliary Surveys - Data Release 2. Machine-learning based classification of sources in the Southern HemisphereCode0
Are deep learning models superior for missing data imputation in large surveys? Evidence from an empirical comparisonCode0
Spatiotemporal Tensor Completion for Improved Urban Traffic Imputation—0
Deep Generative Pattern-Set Mixture Models for Nonignorable MissingnessCode0
A Hamiltonian Monte Carlo Model for Imputation and Augmentation of Healthcare DataCode0
Unsupervised dynamic modeling of medical image transformationCode0
Time-Series Imputation with Wasserstein Interpolation for Optimal Look-Ahead-Bias and Variance Tradeoff—0
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data—0
Misguided Use of Observed Covariates to Impute Missing Covariates in Conditional Prediction: A Shrinkage Problem—0
Composable Generative Models—0
Partially Observed Exchangeable Modeling—0
MAIN: Multihead-Attention Imputation Networks—0
Arbitrary Conditional Distributions with EnergyCode0
Wasserstein Graph Neural Networks for Graphs with Missing Attributes—0
Statistical Inference after Kernel Ridge Regression Imputation under item nonresponse—0
Blind Image Denoising and Inpainting Using Robust Hadamard AutoencodersCode0
Multi-view Integration Learning for Irregularly-sampled Clinical Time SeriesCode0
Anytime 3D Object Reconstruction using Multi-modal Variational Autoencoder—0
Customer Price Sensitivities in Competitive Automobile Insurance Markets—0
Variational manifold learning from incomplete data: application to multislice dynamic MRI—0
Multi-Source Data Fusion for Cyberattack Detection in Power Systems—0
Unsupervised Imputation of Non-ignorably Missing Data Using Importance-Weighted Autoencoders—0
Distances with mixed type variables some modified Gower's coefficients—0
Data-Driven Copy-Paste Imputation for Energy Time SeriesCode0
Mind the wealth gap: a new allocation method to match micro and macro statistics for household wealth—0
Using attention to model long-term dependencies in occupancy behavior—0
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks—0
Artificial Neural Networks to Impute Rounded Zeros in Compositional Data—0
Hard and Soft EM in Bayesian Network Learning from Incomplete DataCode0
Semi-Supervised Off Policy Reinforcement Learning—0
A Data-Driven Analytical Framework of Estimating Multimodal Travel Demand Patterns using Mobile Device Location Data—0
Machine learning with incomplete datasets using multi-objective optimization models—0
Domain Adaptation with Incomplete Target Domains—0
Matrix Inference and Estimation in Multi-Layer ModelsCode0
An Empirical Study of the Downstream Reliability of Pre-Trained Word Embeddings—0
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All datasetsHMNISTPhysioNet Challenge 2012Sprites

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GP-VAE (B-NLST)AUROC0.96—Unverified
#ModelMetricClaimedVerifiedStatus
1GP-VAE (B-NLST)AUROC0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1GP-VAE (B-NLST)MSE0—Unverified