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Synthetic data generation becomes prevalent as a solution to privacy leakage and data shortage.
Causation, prediction, and search
Peter Spirtes, Clark N Glymour, Richard Scheines, and David Heckerman · 2000
Earlier work this paper cites.
Causality
Judea Pearl · 2009
Earlier work this paper cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Generating multi-label discrete patient records using generative adversarial networks
Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F Stewart, and Jimeng Sun · 2017
Earlier work this paper cites.
UCI machine learning repository, 2017
Dheeru Dua and Casey Graff · 2017
Earlier work this paper cites.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
Cited alongside, same era.
Causalgan: Learning causal implicit generative models with adversarial training
Murat Kocaoglu, Christopher Snyder, Alexandros G Dimakis, and Sriram Vishwanath · 2017
Cited alongside, same era.
Privbayes: Private data release via bayesian networks
Jun Zhang, Graham Cormode, Cecilia M Procopiuc, Divesh Srivastava, and Xiaokui Xiao · 2017
Cited alongside, same era.
Generating multi-categorical samples with generative adversarial networks
Ramiro D. Camino, Christian A. Hammerschmidt, and Radu State · 2018
Cited alongside, same era.
Learning functional causal models with generative neural networks
Olivier Goudet, Diviyan Kalainathan, Philippe Caillou, Isabelle Guyon, David Lopez-Paz, and Michele Sebag · 2018
Cited alongside, same era.
Data synthesis based on generative adversarial networks
Noseong Park, Mahmoud Mohammadi, Kshitij Gorde, Sushil Jajodia, Hongkyu Park, and Youngmin Kim · 2018
Later among the works it cites.
Kernel-based approach to handle mixed data for inferring causal graphs
Teny Handhayani and James Cussens · 2019
Later among the works it cites.
Pate-gan: Generating synthetic data with differential privacy guarantees
James Jordon, Jinsung Yoon, and Mihaela van der Schaar · 2019
Later among the works it cites.
Modeling tabular data using conditional gan
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 2019
Later among the works it cites.
Corgan: Correlation-capturing convolutional generative adversarial networks for generating synthetic healthcare records
Amirsina Torfi, , and Edward A. Fox · 2020
Later among the works it cites.
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