| Learnable Prompt as Pseudo-Imputation: Reassessing the Necessity of Traditional EHR Data Imputation in Downstream Clinical Prediction | Jan 30, 2024 | ImputationMissing Values | —Unverified | 0 | 0 |
| Learning Accurate Models on Incomplete Data with Minimal Imputation | Mar 18, 2025 | ImputationMissing Values | —Unverified | 0 | 0 |
| Learning Bayesian networks from demographic and health survey data | Dec 2, 2019 | Missing ValuesSurvey | —Unverified | 0 | 0 |
| Learning Bayesian Networks with Incomplete Data by Augmentation | Aug 27, 2016 | Data AugmentationMissing Values | —Unverified | 0 | 0 |
| Learning Cartesian Product Graphs with Laplacian Constraints | Feb 12, 2024 | Graph LearningImputation | —Unverified | 0 | 0 |
| Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint | Aug 23, 2020 | Graph LearningMissing Values | —Unverified | 0 | 0 |
| Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings | Jun 16, 2022 | ImputationMissing Values | —Unverified | 0 | 0 |
| Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values | Nov 22, 2019 | Missing ValuesMultivariate Time Series Forecasting | —Unverified | 0 | 0 |
| Joint Graph Estimation and Signal Restoration for Robust Federated Learning | May 16, 2025 | Federated LearningGraph Learning | —Unverified | 0 | 0 |
| Learning Representations for Incomplete Time Series Clustering | May 18, 2021 | ClusteringImputation | —Unverified | 0 | 0 |
| Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders | May 9, 2018 | Dimensionality ReductionGeneral Classification | —Unverified | 0 | 0 |
| Learning spatiotemporal features from incomplete data for traffic flow prediction using hybrid deep neural networks | Apr 21, 2022 | ImputationMissing Values | —Unverified | 0 | 0 |
| Learning the Sparse and Low Rank PARAFAC Decomposition via the Elastic Net | May 29, 2017 | Missing Values | —Unverified | 0 | 0 |
| Learning to Treat Sepsis with Multi-Output Gaussian Process Deep Recurrent Q-Networks | Jan 1, 2018 | Deep Reinforcement LearningGaussian Processes | —Unverified | 0 | 0 |
| Leveraging Language Models for Analyzing Longitudinal Experiential Data in Education | Mar 27, 2025 | DecoderMissing Values | —Unverified | 0 | 0 |
| Leveraging Patient Similarity and Time Series Data in Healthcare Predictive Models | Apr 25, 2017 | Change Point DetectionClassification | —Unverified | 0 | 0 |
| Bringing Anatomical Information into Neuronal Network Models | Aug 11, 2020 | Missing ValuesNavigate | —Unverified | 0 | 0 |
| ITI-IQA: a Toolbox for Heterogeneous Univariate and Multivariate Missing Data Imputation Quality Assessment | Jul 16, 2024 | ImputationMissing Values | —Unverified | 0 | 0 |
| Deep Imputation of Missing Values in Time Series Health Data: A Review with Benchmarking | Feb 10, 2023 | BenchmarkingDeep Learning | —Unverified | 0 | 0 |
| Bridging Smart Meter Gaps: A Benchmark of Statistical, Machine Learning and Time Series Foundation Models for Data Imputation | Jan 13, 2025 | ImputationMissing Values | —Unverified | 0 | 0 |
| Iterative missing value imputation based on feature importance | Nov 14, 2023 | Feature ImportanceImputation | —Unverified | 0 | 0 |
| IRTCI: Item Response Theory for Categorical Imputation | Feb 8, 2023 | ImputationMissing Values | —Unverified | 0 | 0 |
| LLM Online Spatial-temporal Signal Reconstruction Under Noise | Nov 24, 2024 | Missing Values | —Unverified | 0 | 0 |
| Irregularly-Sampled Time Series Modeling with Spline Networks | Oct 19, 2022 | Missing ValuesTime Series | —Unverified | 0 | 0 |
| Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values | Mar 1, 2018 | ImputationMissing Values | —Unverified | 0 | 0 |