GAIN: Missing Data Imputation using Generative Adversarial Nets

7 June 2018

Papers citing "GAIN: Missing Data Imputation using Generative Adversarial Nets"

50 / 308 papers shown

Title
Time-series Imputation and Prediction with Bi-Directional Generative Adversarial Networks Mehak Gupta Rahmatollah Beheshti SyDa GAN AI4TS 43 13 0 18 Sep 2020
PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards Masoud Hashemi Ali Fathi AAML 107 32 0 24 Aug 2020
IGANI: Iterative Generative Adversarial Networks for Imputation with Application to Traffic Data A. Kazemi Hadi Meidani 53 20 0 11 Aug 2020
Concept Drift Detection: Dealing with MissingValues via Fuzzy Distance Estimations Anjin Liu Jie Lu Guangquan Zhang 162 15 0 09 Aug 2020
CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19 Zhaozhi Qian Ahmed Alaa Mihaela van der Schaar 81 41 0 27 Jul 2020
Instructions and Guide for Diagnostic Questions: The NeurIPS 2020 Education Challenge Zichao Wang A. Lamb Evgeny S. Saveliev Pashmina Cameron Yordan Zaykov ... Richard G. Baraniuk Craig Barton Simon L. Peyton Jones Simon Woodhead Cheng Zhang AI4Ed 100 81 0 23 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 177 1,020 0 16 Jul 2020
Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows Chris Cannella Mohammadreza Soltani Vahid Tarokh BDL 83 0 0 13 Jul 2020
Graph Convolutional Networks for Graphs Containing Missing Features Hibiki Taguchi Xin Liu T. Murata GNN 121 98 0 09 Jul 2020
NeuMiss networks: differentiable programming for supervised learning with missing values Marine Le Morvan Julie Josse Thomas Moreau Erwan Scornet Gaël Varoquaux 88 8 0 03 Jul 2020
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data F. Tonolini Pablo G. Moreno Andreas C. Damianou Roderick Murray-Smith 42 1 0 30 Jun 2020
Learning Disentangled Representations of Video with Missing Data Armand Comas Massague Fangqiu Yi Z. Feric Mario Sznaier Rose Yu DRL 63 16 0 23 Jun 2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data Niels Bruun Ipsen Pierre-Alexandre Mattei J. Frellsen DRL 74 57 0 23 Jun 2020
Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network Magda Friedjungová Daniel Vasata Maksym Balatsko M. Jiřina DiffM SyDa GAN 75 12 0 21 Jun 2020
Bayesian Optimization with Missing Inputs P. Luong Dang Nguyen Sunil R. Gupta Santu Rana Svetha Venkatesh 72 3 0 19 Jun 2020
On the Learnability of Concepts: With Applications to Comparing Word Embedding Algorithms Adam Sutton N. Cristianini 59 8 0 17 Jun 2020
Causal Discovery from Incomplete Data using An Encoder and Reinforcement Learning Xiaoshui Huang Fujin Zhu Lois Holloway Ali Haidar CML 63 10 0 09 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 106 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 74 7 0 13 May 2020
Minority Class Oversampling for Tabular Data with Deep Generative Models R. Camino Christian A. Hammerschmidt R. State 72 2 0 07 May 2020
MCFlow: Monte Carlo Flow Models for Data Imputation Trevor W. Richardson Wencheng Wu Lei Lin Beilei Xu Edgar A. Bernal OOD 93 48 0 27 Mar 2020
Incomplete Graph Representation and Learning via Partial Graph Neural Networks Bo Jiang Ziyan Zhang AI4CE GNN 146 19 0 23 Mar 2020
Blur, Noise, and Compression Robust Generative Adversarial Networks Takuhiro Kaneko Tatsuya Harada 99 17 0 17 Mar 2020
Unified Multi-Domain Learning and Data Imputation using Adversarial Autoencoder André Mendes Julian Togelius L. Coelho 57 2 0 15 Mar 2020
Missing Data Imputation using Optimal Transport Boris Muzellec Julie Josse Claire Boyer Marco Cuturi OT 87 127 0 10 Feb 2020
Linear predictor on linearly-generated data with missing values: non consistency and solutions Marine Le Morvan Nicolas Prost Julie Josse Erwan Scornet Gaël Varoquaux 92 26 0 03 Feb 2020
Causal Discovery from Incomplete Data: A Deep Learning Approach Yuhao Wang Vlado Menkovski Hao Wang Xin Du Mykola Pechenizkiy CML 85 35 0 15 Jan 2020
Robust Multi-Output Learning with Highly Incomplete Data via Restricted Boltzmann Machines G. Fissore A. Decelle Cyril Furtlehner Yufei Han OOD 38 8 0 19 Dec 2019
Graph Markov Network for Traffic Forecasting with Missing Data Zhiyong Cui Longfei Lin Ziyuan Pu Yinhai Wang AI4TS 66 97 0 10 Dec 2019
Perception-Distortion Trade-off with Restricted Boltzmann Machines Chris Cannella Jie Ding Mohammadreza Soltani Vahid Tarokh 60 0 0 21 Oct 2019
Learning Neural Causal Models from Unknown Interventions Nan Rosemary Ke O. Bilaniuk Anirudh Goyal Stefan Bauer Hugo Larochelle Bernhard Schölkopf Michael C. Mozer C. Pal Yoshua Bengio CML OOD 131 170 0 02 Oct 2019
Regularising Deep Networks with Deep Generative Models M. Willetts A. Camuto Stephen J. Roberts Chris Holmes UQCV 36 0 0 25 Sep 2019
Flow Models for Arbitrary Conditional Likelihoods Yongqian Li Shoaib Akbar Junier B. Oliva OOD AI4CE 83 40 0 13 Sep 2019
Recovery of Future Data via Convolution Nuclear Norm Minimization Guangcan Liu Wayne Zhang AI4TS 87 20 0 06 Sep 2019
GP-VAE: Deep Probabilistic Time Series Imputation Vincent Fortuin Dmitry Baranchuk Gunnar Rätsch Stephan Mandt BDL AI4TS 158 259 0 09 Jul 2019
Efficient data augmentation using graph imputation neural networks Indro Spinelli Simone Scardapane M. Scarpiniti A. Uncini 26 5 0 20 Jun 2019
ASAC: Active Sensing using Actor-Critic models Chang Jo Kim James Jordon M. Schaar CML 74 16 0 16 Jun 2019
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks Joonyoung Yi Juhyuk Lee Kwang Joon Kim Sung Ju Hwang Eunho Yang VLM 71 23 0 01 Jun 2019
Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators Daniel Stoller Sebastian Ewert S. Dixon GAN 60 5 0 29 May 2019
Generative Imputation and Stochastic Prediction Mohammad Kachuee Kimmo Karkkainen Orpaz Goldstein Sajad Darabi Majid Sarrafzadeh 104 24 0 22 May 2019
Missing Data Imputation with Adversarially-trained Graph Convolutional Networks Indro Spinelli Simone Scardapane A. Uncini MedIm AI4CE 91 155 0 06 May 2019
Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models Lukasz Struski M. Sadowski Tomasz Danel Jacek Tabor Igor T. Podolak DiffM 94 7 0 06 Apr 2019
Unsupervised Data Imputation via Variational Inference of Deep Subspaces Adrian Dalca John Guttag M. Sabuncu DRL 69 13 0 08 Mar 2019
Variational Auto-Decoder: A Method for Neural Generative Modeling from Incomplete Data Amir Zadeh Y. Lim Paul Pu Liang Louis-Philippe Morency DRL 82 16 0 03 Mar 2019
Improving Missing Data Imputation with Deep Generative Models R. Camino Christian A. Hammerschmidt R. State SyDa 91 56 0 27 Feb 2019
HexaGAN: Generative Adversarial Nets for Real World Classification Uiwon Hwang Dahuin Jung Sungroh Yoon GAN 67 37 0 26 Feb 2019
MisGAN: Learning from Incomplete Data with Generative Adversarial Networks Steven Cheng-Xian Li Bo Jiang Benjamin M. Marlin GAN SyDa 74 171 0 25 Feb 2019
Learning about an exponential amount of conditional distributions Mohamed Ishmael Belghazi Maxime Oquab Yann LeCun David Lopez-Paz BDL SSL 74 28 0 22 Feb 2019
On the consistency of supervised learning with missing values Julie Josse Jacob M. Chen Nicolas Prost Erwan Scornet Gaël Varoquaux 154 115 0 19 Feb 2019
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation Yukai Liu Rose Yu Stephan Zheng Eric Zhan Yisong Yue BDL AI4TS 127 117 0 30 Jan 2019