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Generative adversarial networks (GANs) are an expressive class of neural generative models with tremendous success in modeling high-dimensional continuous measures.
On the translocation of masses
Leonid V. Kantorovich · 1942
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Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization
XuanLong Nguyen, Martin J. Wainwright, and Michael I. Jordan · 2008
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GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Eran Eden, Roy Navon, Israel Steinfeld, Doron Lipson, and Zohar Yakhini · 2009
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
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Auto-encoding variational Bayes
Diederik P. Kingma and Max Welling · 2013
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Domain adaptation with regularized optimal transport
Nicolas Courty, Rémi Flamary, and Devis Tuia · 2014
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Regularized discrete optimal transport
Sira Ferradans, Nicolas Papadakis, Gabriel Peyré, and Jean-François Aujol · 2014
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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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Unbalanced optimal transport: geometry and Kantorovich formulation
Lenaic Chizat, Gabriel Peyré, Bernhard Schmitzer, and François-Xavier Vialard · 2015
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Learning with a Wasserstein loss
Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya, and Tomaso A Poggio · 2015
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Convolutional wasserstein distances: Efficient optimal transportation on geometric domains
Justin Solomon, Fernando De Goes, Gabriel Peyré, Marco Cuturi, Adrian Butscher, Andy Nguyen, Tao Du, and Leonidas Guibas · 2015
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Scaling algorithms for unbalanced transport problems
Lenaic Chizat, Gabriel Peyré, Bernhard Schmitzer, and François-Xavier Vialard · 2016
Cited alongside, same era.
Stochastic optimization for large-scale optimal transport
Aude Genevay, Marco Cuturi, Gabriel Peyré, and Francis Bach · 2016
Cited alongside, same era.
Dual learning for machine translation
Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tieyan Liu, and Wei-Ying Ma · 2016
Cited alongside, same era.
A new optimal transport distance on the space of finite Radon measures
Stanislav Kondratyev, Léonard Monsaingeon, Dmitry Vorotnikov, et al · 2016
Cited alongside, same era.
f-GAN: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
Cited alongside, same era.
Reconstruction of developmental landscapes by optimal-transport analysis of single-cell gene expression sheds light on cellular reprogramming
Geoffrey Schiebinger, Jian Shu, Marcin Tabaka, Brian Cleary, Vidya Subramanian, Aryeh Solomon, Siyan Liu, Stacie Lin, Peter Berube, Lia Lee, et al · 2017
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Large-scale optimal transport and mapping estimation
Vivien Seguy, Bharath Bhushan Damodaran, Rémi Flamary, Nicolas Courty, Antoine Rolet, and Mathieu Blondel · 2017
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Dualgan: Unsupervised dual learning for image-to-image translation
Zili Yi, Hao (Richard) Zhang, Ping Tan, and Minglun Gong · 2017
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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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Augmented cyclegan: Learning many-to-many mappings from unpaired data
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Martin Arjovsky and Léon Bottou · 2017
Cited alongside, same era.
Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Smooth and sparse optimal transport
Mathieu Blondel, Vivien Seguy, and Antoine Rolet · 2017
Cited alongside, same era.
Unsupervised pixel-level domain adaptation with generative adversarial networks
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, and Dilip Krishnan · 2017
Cited alongside, same era.
A tumor growth model of Hele-Shaw type as a gradient flow
Lénaïc Chizat and Simone Di Marino · 2017
Cited alongside, same era.
Optimal transport for domain adaptation
Nicolas Courty, Rémi Flamary, Devis Tuia, and Alain Rakotomamonjy · 2017
Cited alongside, same era.
Improved training of Wasserstein GANS
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
Cited alongside, same era.
Amjad Almahairi, Sai Rajeswar, Alessandro Sordoni, Philip Bachman, and Aaron Courville · 2018
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Magan: Aligning biological manifolds
Matthew Amodio and Smita Krishnaswamy · 2018
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An interpolating distance between optimal transport and Fisher–Rao metrics
Lenaic Chizat, Gabriel Peyré, Bernhard Schmitzer, and François-Xavier Vialard · 2018
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Real Analysis and Probability: 0
Richard M. Dudley · 2018
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Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis
Jeffrey A. Farrell, Yiqun Wang, Samantha J. Riesenfeld, Karthik Shekhar, Aviv Regev, and Alexander F. Schier · 2018
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Deepmatch: Balancing deep covariate representations for causal inference using adversarial training
Nathan Kallus · 2018
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Optimal entropy-transport problems and a new Hellinger–Kantorovich distance between positive measures
Matthias Liero, Alexander Mielke, and Giuseppe Savaré · 2018
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Which training methods for GANs do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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