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arXiv · 1811.06763

Entropy-regularized Optimal Transport Generative Models

Dong Liu·Minh Thành Vu·Saikat Chatterjee·Lars K. Rasmussen
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Abstract

We investigate the use of entropy-regularized optimal transport (EOT) cost in developing generative models to learn implicit distributions. Two generative models are proposed. One uses EOT cost directly in an one-shot optimization problem and the other uses EOT cost iteratively in an adversarial game. The proposed generative models show improved performance over contemporary models for image generation on MNSIT.

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Dong Liu, Minh Thành Vu, Saikat Chatterjee, Lars K. Rasmussen. 2018-11-16. Entropy-regularized Optimal Transport Generative Models. https://doi.org/10.1109/icassp.2019.8682721

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