2017

GAN and VAE from an Optimal Transport Point of View

Genevay, Aude, Peyré, Gabriel, Cuturi, Marco

Understand

This short article revisits some of the ideas introduced in arXiv:1701.07875 and arXiv:1705.07642 in a simple setup.

  • This sheds some lights on the connexions between Variational Autoencoders (VAE), Generative Adversarial Networks (GAN) and Minimum Kantorovitch Estimators (MKE).

Built on

  • On minimum Kantorovich distance estimators

    Federico Bassetti, Antonella Bodini, and Eugenio Regazzini · 2006

    Earlier work this paper cites.

  • Optimal transport: old and new

    Cédric Villani · 2008

    Earlier work this paper cites.

  • Auto-encoding variational bayes

    Diederik P. Kingma and Max Welling · 2013

    Earlier work this paper cites.

  • Generative adversarial nets

    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.

Similar

  • Optimal transport for applied mathematicians

    Filippo Santambrogio · 2015

    Cited alongside, same era.

  • Scaling algorithms for unbalanced transport problems

    Lenaic Chizat, Gabriel Peyré, Bernhard Schmitzer, and Fancois-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.

  • Wasserstein training of restricted Boltzmann machines

    Grégoire Montavon, Klaus-Robert Müller, and Marco Cuturi · 2016

    Cited alongside, same era.

  • Mémoire sur la théorie des déblais et des remblais

    Gaspard Monge

    Cited in the paper.

Then

  • Wasserstein GAN

    Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017

    Closest in time.

  • Inference in generative models using the Wasserstein distance

    Original

    Espen Bernton, Pierre E Jacob, Mathieu Gerber, and Christian P Robert · 2017

    Closest in time.

  • From optimal transport to generative modeling: the VEGAN cookbook

    Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin, Carl-Johann Simon-Gabriel, and Bernhard Schoelkopf · 2017

    Closest in time.

  • Sinkhorn-autodiff: Tractable Wasserstein learning of generative models

    Aude Genevay, Gabriel Peyré, and Marco Cuturi · 2017

    Closest in time.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…