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On gradient regularizers for MMD GANs

Arbel, M; Sutherland, DJ; Bińkowski, M; Gretton, A; (2018) On gradient regularizers for MMD GANs. In: Bengio, S and Wallach, H and Larochelle, H and Grauman, K and Cesa-Bianchi, N and Garnett, R, (eds.) Advances in Neural Information Processing Systems 31 (NIPS 2018). NIPS Proceedings: Montreal, Canada. Green open access

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Abstract

We propose a principled method for gradient-based regularization of the critic of GAN-like models trained by adversarially optimizing the kernel of a Maximum Mean Discrepancy (MMD). We show that controlling the gradient of the critic is vital to having a sensible loss function, and devise a method to enforce exact, analytical gradient constraints at no additional cost compared to existing approximate techniques based on additive regularizers. The new loss function is provably continuous, and experiments show that it stabilizes and accelerates training, giving image generation models that outperform state-of-the art methods on 160 × 160 CelebA and 64 × 64 unconditional ImageNet.

Type: Proceedings paper
Title: On gradient regularizers for MMD GANs
Event: Neural Information Processing Systems 2018
Location: Montreal, Canada
Dates: 03 December 2018 - 09 December 2018
Open access status: An open access version is available from UCL Discovery
Publisher version: https://papers.nips.cc/book/advances-in-neural-inf...
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10062885
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