Handling Incomplete Heterogeneous Data using VAEs

10 July 2018

Papers citing "Handling Incomplete Heterogeneous Data using VAEs"

50 / 55 papers shown

Title
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 66 0 0 21 Apr 2025
Robust Simulation-Based Inference under Missing Data via Neural Processes Yogesh Verma Ayush Bharti Vikas K. Garg 70 0 0 03 Mar 2025
Developing robust methods to handle missing data in real-world applications effectively Youran Zhou Mohamed Reda Bouadjenek Sunil Arya 44 0 0 27 Feb 2025
Boundary-enhanced time series data imputation with long-term dependency diffusion models Chunjing Xiao Xue Jiang Xianghe Du Wei Yang Wei Lu Xinyu Wang Kevin Chetty 52 1 0 11 Jan 2025
Handling Incomplete Heterogeneous Data using a Data-Dependent Kernel Youran Zhou Mohamed Reda Bouadjenek Jonathan R. Wells Sunil Aryal 33 0 0 08 Jan 2025
Multi-scale Temporal Fusion Transformer for Incomplete Vehicle Trajectory Prediction Zhanwen Liu Chao Li Yang Wang Nan Yang Xing Fan Jiaqi Ma Xiangmo Zhao 32 2 0 02 Sep 2024
DALL-M: Context-Aware Clinical Data Augmentation with LLMs Chihcheng Hsieh Catarina Moreira Isabel Blanco Nobre Sandra Costa Sousa Chun Ouyang M. Brereton Joaquim A. Jorge Jacinto C. Nascimento 54 0 0 11 Jul 2024
Flexible inference in heterogeneous and attributed multilayer networks Martina Contisciani Marius Hobbhahn Eleanor A. Power Philipp Hennig Caterina De Bacco 37 1 0 31 May 2024
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families Vaidotas Šimkus Michael U. Gutmann 43 2 0 05 Mar 2024
MINTY: Rule-based Models that Minimize the Need for Imputing Features with Missing Values Lena Stempfle Fredrik D. Johansson 32 2 0 23 Nov 2023
Unmasking the Chameleons: A Benchmark for Out-of-Distribution Detection in Medical Tabular Data Mohammad Azizmalayeri Ameen Abu-Hanna Dirk Kraft OOD 28 5 0 28 Sep 2023
Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics Kenta Oono Nontawat Charoenphakdee K. Bito Zhengyan Gao Yoshiaki Ota ... Kohei Hayashi Yuki Saito Koki Tsuda Hiroshi Maruyama K. Hayashi 40 1 0 19 Jun 2023
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders Dingsu Wang Yuchen Yan Ruizhong Qiu Yada Zhu Kaiyu Guan A. Margenot Hanghang Tong AI4TS 43 27 0 29 May 2023
Synthetic data generation for a longitudinal cohort study -- Evaluation, method extension and reproduction of published data analysis results Lisa Kühnel Julian Schneider Ines Perrar Tim Adams F. Prasser U. Nöthlings Holger Fröhlich Juliane Fluck 35 5 0 12 May 2023
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models Irene Balelli Aude Sportisse Francesco Cremonesi Pierre-Alexandre Mattei Marco Lorenzi 34 3 0 17 Apr 2023
Transformed Distribution Matching for Missing Value Imputation He Zhao Ke Sun Amir Dezfouli Edwin V. Bonilla 34 19 0 20 Feb 2023
$Ae^2I$ : A Double Autoencoder for Imputation of Missing Values Fuchang Gao 24 1 0 16 Jan 2023
Predictive World Models from Real-World Partial Observations Robin Karlsson Alexander Carballo Keisuke Fujii Kento Ohtani K. Takeda 35 5 0 12 Jan 2023
Data Imputation with Iterative Graph Reconstruction J. Zhong Weiwei Ye Ning Gui 11 12 0 06 Dec 2022
$β$ -Multivariational Autoencoder for Entangled Representation Learning in Video Frames F. Nouri R. Bergevin 16 0 0 22 Nov 2022
Diffusion models for missing value imputation in tabular data Shuhan Zheng Nontawat Charoenphakdee VLM DiffM 32 68 0 31 Oct 2022
Reverse Survival Model (RSM): A Pipeline for Explaining Predictions of Deep Survival Models Mohammadreza Rezaei Reza Saadati Fard Ebrahim Pourjafari Navid Ziaei Amir Sameizadeh M. Shafiee M. Alavinia M. Abolghasemian Nick Sajadi 33 1 0 27 Oct 2022
TabDDPM: Modelling Tabular Data with Diffusion Models Akim Kotelnikov Dmitry Baranchuk Ivan Rubachev Artem Babenko DiffM 75 239 0 30 Sep 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data Timur Sattarov Dayananda Herurkar Jörn Hees 30 8 0 21 Sep 2022
Sharing pattern submodels for prediction with missing values Lena Stempfle Ashkan Panahi Fredrik D. Johansson 22 6 0 22 Jun 2022
Mitigating Modality Collapse in Multimodal VAEs via Impartial Optimization Adrián Javaloy Maryam Meghdadi Isabel Valera 27 27 0 09 Jun 2022
PROMISSING: Pruning Missing Values in Neural Networks S. M. Kia N. M. Rad Dan Opstal B. V. Schie A. Marquand J. Pluim W. Cahn H. Schnack VLM 35 4 0 03 Jun 2022
Explainable Data Imputation using Constraints Sandeep Hans Diptikalyan Saha Aniya Aggarwal 14 5 0 10 May 2022
Learning Conditional Variational Autoencoders with Missing Covariates S. Ramchandran Gleb Tikhonov Otto Lönnroth Pekka Tiikkainen Harri Lähdesmäki CML 19 14 0 02 Mar 2022
Model-agnostic out-of-distribution detection using combined statistical tests Federico Bergamin Pierre-Alexandre Mattei Jakob Drachmann Havtorn Hugo Senetaire Hugo Schmutz Lars Maaløe Søren Hauberg J. Frellsen OODD 24 18 0 02 Mar 2022
SAITS: Self-Attention-based Imputation for Time Series Wenjie Du David Cote Yong-Jin Liu AI4TS 21 230 0 17 Feb 2022
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo I. Peis Chao Ma José Miguel Hernández-Lobato BDL DRL 16 14 0 09 Feb 2022
Maximizing information from chemical engineering data sets: Applications to machine learning Alexander Thebelt Johannes Wiebe Jan Kronqvist Calvin Tsay Ruth Misener AI4CE 42 68 0 25 Jan 2022
Multi-task longitudinal forecasting with missing values on Alzheimer's Disease C. Sevilla-Salcedo Vandad Imani Pablo Martínez Olmos Vanessa Gómez-Verdejo Jussi Tohka 26 8 0 13 Jan 2022
Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma Cheng Zhang 36 34 0 27 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 45 648 0 05 Oct 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 40 33 0 09 Jul 2021
Learning Multimodal VAEs through Mutual Supervision Thomas Joy Yuge Shi Philip Torr Tom Rainforth Sebastian M. Schmon N. Siddharth SSL 32 20 0 23 Jun 2021
Tiny Transformers for Environmental Sound Classification at the Edge David Elliott Carlos E. Otero Steven Wyatt Evan Martino 21 15 0 22 Mar 2021
Unsupervised Learning of Global Factors in Deep Generative Models I. Peis Pablo Martínez Olmos Antonio Artés-Rodríguez BDL DRL 29 8 0 15 Dec 2020
Sparse Gaussian Process Variational Autoencoders Matthew Ashman Jonathan So Will Tebbutt Vincent Fortuin Michael Pearce Richard Turner 24 33 0 20 Oct 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 25 85 0 23 Jun 2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data Niels Bruun Ipsen Pierre-Alexandre Mattei J. Frellsen DRL 14 54 0 23 Jun 2020
Variational Variance: Simple, Reliable, Calibrated Heteroscedastic Noise Variance Parameterization Andrew Stirn David A. Knowles DRL 18 10 0 08 Jun 2020
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins? Jeremy Georges-Filteau Elisa Cirillo SyDa AI4CE 36 17 0 27 May 2020
Multiple Imputation for Biomedical Data using Monte Carlo Dropout Autoencoders Kristian Miok Dong Nguyen Doan Marko Robnik-Šikonja D. Zaharie SyDa 34 7 0 13 May 2020
Uncertainty-Aware Variational-Recurrent Imputation Network for Clinical Time Series A. Mulyadi E. Jun Heung-Il Suk BDL 67 57 0 02 Mar 2020
Learning Model-Agnostic Counterfactual Explanations for Tabular Data Martin Pawelczyk Johannes Haug Klaus Broelemann Gjergji Kasneci OOD CML 33 199 0 21 Oct 2019
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data Simao Eduardo A. Nazábal Christopher K. I. Williams Charles Sutton DRL 16 32 0 15 Jul 2019
GP-VAE: Deep Probabilistic Time Series Imputation Vincent Fortuin Dmitry Baranchuk Gunnar Rätsch Stephan Mandt BDL AI4TS 19 245 0 09 Jul 2019