SOTAVerified

Imputation

Substituting missing data with values according to some criteria.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 751–775 of 1237 papers

TitleStatusHype
Generative Trees: Adversarial and Copycat—0
Semi-Supervised Quantile Estimation: Robust and Efficient Inference in High Dimensional Settings—0
Dense Air Quality Maps Using Regressive Facility Location Based Drive By Sensing—0
Deep Attention-Based Supernovae Classification of Multi-Band Light-Curves—0
Evaluation of data imputation strategies in complex, deeply-phenotyped data sets: the case of the EU-AIMS Longitudinal European Autism Project—0
Variational Bayesian Filtering with Subspace Information for Extreme Spatio-Temporal Matrix Completion—0
Time Series Generation with Masked AutoencoderCode1
Imputing Missing Observations with Time Sliced Synthetic Minority Oversampling Technique—0
A Kernel-Expanded Stochastic Neural NetworkCode0
Multi-task longitudinal forecasting with missing values on Alzheimer's Disease—0
Differentiable and Scalable Generative Adversarial Models for Data Imputation—0
Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems—0
Model-based Clustering with Missing Not At Random DataCode0
DeepFIB: Self-Imputation for Time Series Anomaly Detection—0
On the Relation between Prediction and Imputation Accuracy under Missing Covariates—0
Federated-EM with heterogeneity mitigation and variance reduction—0
Auditing Black-Box Prediction Models for Data Minimization ComplianceCode0
What’s a good imputation to predict with missing values?—0
Improving random walk rankings with feature selection and imputationCode0
A Recommender System-Inspired Cloud Data Filling Scheme for Satellite-based Coastal Observation—0
Data imputation and comparison of custom ensemble models with existing libraries like XGBoost, Scikit learn, etc. for Predictive Equipment failure—0
A Graph-based Imputation Method for Sparse Medical Records—0
MIRACLE: Causally-Aware Imputation via Learning Missing Data MechanismsCode1
Convolutional generative adversarial imputation networks for spatio-temporal missing data in storm surge simulations—0
Federated Expectation Maximization with heterogeneity mitigation and variance reduction—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