SOTAVerified

Imputation

Substituting missing data with values according to some criteria.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 526–550 of 1237 papers

TitleStatusHype
Convolutional Imputation of Matrix Networks—0
A Time Series Multitask Framework Integrating a Large Language Model, Pre-Trained Time Series Model, and Knowledge Graph—0
A Missing Value Filling Model Based on Feature Fusion Enhanced Autoencoder—0
AdaWaveNet: Adaptive Wavelet Network for Time Series Analysis—0
Generalised learning of time-series: Ornstein-Uhlenbeck processes—0
General Causal Imputation via Synthetic Interventions—0
Convolutional generative adversarial imputation networks for spatio-temporal missing data in storm surge simulations—0
GEDI: A Graph-based End-to-end Data Imputation Framework—0
Convolutional Bipartite Attractor Networks—0
A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches—0
Gaussian process imputation of multiple financial series—0
Convergence Properties of Kronecker Graphical Lasso Algorithms—0
GATGPT: A Pre-trained Large Language Model with Graph Attention Network for Spatiotemporal Imputation—0
Controllable Missingness from Uncontrollable Missingness: Joint Learning Measurement Policy and Imputation—0
A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining—0
Anytime 3D Object Reconstruction using Multi-modal Variational Autoencoder—0
GANravel: User-Driven Direction Disentanglement in Generative Adversarial Networks—0
GAMIN: Generative Adversarial Multiple Imputation Network for Highly Missing Data—0
Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit—0
FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection—0
FragmGAN: Generative Adversarial Nets for Fragmentary Data Imputation and Prediction—0
Continuous-time Autoencoders for Regular and Irregular Time Series Imputation—0
Contextual HyperNetworks for Novel Feature Adaptation—0
A data imputation method for multivariate time series based on generative adversarial network—0
A Causal Convolutional Low-rank Representation Model for Imputation of Water Quality Data—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