Dec 1, 2020 · We introduce Discriminator Gradient flow (DGflow), a new technique that improves generated samples via the gradient flow of entropy-regularized ...
Jan 12, 2021 · One-sentence Summary: A method of refining samples from deep generative models using the discriminator gradient flow of f-divergences.
In this paper, Discriminator Gradient flow (DG flow) is introduced as a method that completely removes the above restrictions. DG flow is used to refine samples ...
We introduce Discriminator Gradient flow (DGflow), a new technique that improves generated samples via the gradient flow of entropy-regularized f-divergences ...
Empirical results demonstrate that DGflow leads to significant improvement in the quality of generated samples for a variety of generative models, ...
Jun 5, 2021 · In this work, we present a method using gradient flows of entropy-regularized f-divergences for refining samples from deep generative models ...
Our technique, Discriminator Gradient $f$low (DG$f$low), refines samples from GANs (and other deep generative models such as VAEs and normalizing flows!).
Jan 29, 2021 · In this paper, we propose DGflow, a technique to improve samples from deep generative models using the gradient flow of entropy-regularized f- ...
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Dec 1, 2020 · Empirical results demonstrate that DGflow leads to significant improvement in the quality of generated samples for a variety of generative ...
Refining deep generative models via dis- criminator gradient flow. In ICLR ... Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport ...