data imputation

Retrieval-Based Transformer for Table Augmentation ACL 2023 To Impute or not to Impute? Missing Data in Treatment Effect Estimation AISTATS 2023 Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values AAAI 2022 MM-Align: Learning Optimal Transport-based Alignment Dynamics for Fast and Accurate Inference on Missing Modality Sequences EMNLP 2022 Survival Seq2Seq: A Survival Model based on Sequence to Sequence Architecture MLHC 2022 Identifiable Generative models for Missing Not at Random Data Imputation NeurIPS 2021 Longitudinal Variational Autoencoder AISTATS 2021 Multi-version Tensor Completion for Time-delayed Spatio-temporal Data IJCAI 2021 Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks (Student Abstract) AAAI 2021 Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data AISTATS 2021 Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random Data NeurIPS 2020 GAMIN: Generative Adversarial Multiple Imputation Network for Highly Missing Data CVPR 2020 McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020 Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data AISTATS 2020 MisGAN: Learning from Incomplete Data with Generative Adversarial Networks ICLR 2019 MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ICML 2019 Processing of missing data by neural networks NeurIPS 2018 Input Convex Neural Networks ICML 2017 A Paradigm for Building Generalized Models of Human Image Perception Through Data Fusion CVPR 2016 Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series MLHC 2016 Data Generation as Sequential Decision Making NeurIPS 2015 Multimodal Learning with Deep Boltzmann Machines JMLR 2014