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FragmGAN: Generative Adversarial Nets for Fragmentary Data Imputation
  and Prediction

FragmGAN: Generative Adversarial Nets for Fragmentary Data Imputation and Prediction

9 March 2022
Fang Fang
Shenliao Bao
    AI4CEGAN
ArXiv (abs)PDFHTML

Papers citing "FragmGAN: Generative Adversarial Nets for Fragmentary Data Imputation and Prediction"

13 / 13 papers shown
Title
Variational Selective Autoencoder: Learning from Partially-Observed
  Heterogeneous Data
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Yu Gong
Hossein Hajimirsadeghi
Jiawei He
Thibaut Durand
Greg Mori
CML
55
11
0
25 Feb 2021
IFGAN: Missing Value Imputation using Feature-specific Generative
  Adversarial Networks
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks
Wei Qiu
Yangsibo Huang
Quanzheng Li
GAN
24
5
0
23 Dec 2020
Imputation of Missing Data with Class Imbalance using Conditional
  Generative Adversarial Networks
Imputation of Missing Data with Class Imbalance using Conditional Generative Adversarial Networks
S. Awan
Bennamoun
Ferdous Sohel
Frank M. Sanfilippo
Girish Dwivedi
GANAI4CE
34
63
0
01 Dec 2020
Handling Missing Data with Graph Representation Learning
Handling Missing Data with Graph Representation Learning
Jiaxuan You
Xiaobai Ma
D. Ding
Mykel Kochenderfer
J. Leskovec
66
181
0
30 Oct 2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Bruun Ipsen
Pierre-Alexandre Mattei
J. Frellsen
DRL
44
57
0
23 Jun 2020
MCFlow: Monte Carlo Flow Models for Data Imputation
MCFlow: Monte Carlo Flow Models for Data Imputation
Trevor W. Richardson
Wencheng Wu
Lei Lin
Beilei Xu
Edgar A. Bernal
OOD
60
48
0
27 Mar 2020
Integrative Factor Regression and Its Inference for Multimodal Data
  Analysis
Integrative Factor Regression and Its Inference for Multimodal Data Analysis
Quefeng Li
Lexin Li
64
27
0
11 Nov 2019
Missing Not at Random in Matrix Completion: The Effectiveness of
  Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
Wei-Ying Ma
George H. Chen
118
52
0
28 Oct 2019
Improving Missing Data Imputation with Deep Generative Models
Improving Missing Data Imputation with Deep Generative Models
R. Camino
Christian A. Hammerschmidt
R. State
SyDa
53
55
0
27 Feb 2019
GAIN: Missing Data Imputation using Generative Adversarial Nets
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon
James Jordon
M. Schaar
GAN
63
1,026
0
07 Jun 2018
Variational Autoencoder with Arbitrary Conditioning
Variational Autoencoder with Arbitrary Conditioning
Oleg Ivanov
Michael Figurnov
Dmitry Vetrov
BDLDRL
59
147
0
06 Jun 2018
MIDA: Multiple Imputation using Denoising Autoencoders
MIDA: Multiple Imputation using Denoising Autoencoders
Lovedeep Gondara
Ke Wang
AI4CE
91
85
0
08 May 2017
MissForest - nonparametric missing value imputation for mixed-type data
MissForest - nonparametric missing value imputation for mixed-type data
D. Stekhoven
Peter Buhlmann
233
4,330
0
04 May 2011
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