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We propose a generative Causal Adversarial Network (CAN) for learning and sampling from conditional and interventional distributions.
Nonlinear programming. athena scientific
Dimitri P Bertsekas · 1999
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A bayesian approach to causal discovery
David Heckerman, Christopher Meek, and Gregory Cooper · 1999
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Causation, prediction, and search
Peter Spirtes, Clark N Glymour, Richard Scheines, and David Heckerman · 2000
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Optimal structure identification with greedy search
David Maxwell Chickering · 2002
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The max-min hill-climbing bayesian network structure learning algorithm
Ioannis Tsamardinos, Laura E Brown, and Constantin F Aliferis · 2006
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Causality: Models, Reasoning and Inference
Judea Pearl · 2009
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Identifiability of causal graphs using functional models
Jonas Peters, Joris Mooij, Dominik Janzing, and Bernhard Schölkopf · 2012
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Lecture 6.5—RmsProp: Divide the gradient by a running average of its recent magnitude
T. Tieleman and G. Hinton · 2012
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Rectifier nonlinearities improve neural network acoustic models
Andrew L Maas, Awni Y Hannun, and Andrew Y Ng · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Causal discovery with continuous additive noise models
Jonas Peters, Joris M Mooij, Dominik Janzing, and Bernhard Schölkopf · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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A note on the evaluation of generative models
Lucas Theis, Aäron van den Oord, and Matthias Bethge · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Coupled generative adversarial networks
Ming-Yu Liu and Oncel Tuzel · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Seqgan: Sequence generative adversarial nets with policy gradient
Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu · 2017
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Conditional image synthesis with auxiliary classifier gans
Augustus Odena, Christopher Olah, and Jonathon Shlens · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
Discovering causal signals in images
David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Scholkopf, and Léon Bottou · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Mocogan: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
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Generating multi-categorical samples with generative adversarial networks
Ramiro Camino, Christian Hammerschmidt, and Radu State · 2018
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How good is my gan?
Konstantin Shmelkov, Cordelia Schmid, and Karteek Alahari · 2018
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Causalgan: Learning causal implicit generative models with adversarial training
Murat Kocaoglu, Christopher Snyder, Alexandros G Dimakis, and Sriram Vishwanath · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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NIPS 2016 tutorial: Generative adversarial networks
Ian J. Goodfellow · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schölkopf, and Clark Glymour · 2018
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Jointgan: Multi-domain joint distribution learning with generative adversarial nets
Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, and Lawrence Carin · 2018
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Dags with no tears: Continuous optimization for structure learning
Xun Zheng, Bryon Aragam, Pradeep K Ravikumar, and Eric P Xing · 2018
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Is generator conditioning causally related to gan performance?
Augustus Odena, Jacob Buckman, Catherine Olsson, Tom B Brown, Christopher Olah, Colin Raffel, and Ian Goodfellow · 2018
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Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis
Minfeng Zhu, Pingbo Pan, Wei Chen, and Yi Yang · 2019
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Gradient-based neural dag learning
Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu, and Simon Lacoste-Julien · 2019
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Dag-gnn: Dag structure learning with graph neural networks
Yue Yu, Jie Chen, Tian Gao, and Mo Yu · 2019
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Causal discovery with reinforcement learning
Shengyu Zhu and Zhitang Chen · 2019
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Causal discovery toolbox: Uncover causal relationships in python
Diviyan Kalainathan and Olivier Goudet · 2019
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