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stat.ML2023★ 1 cited
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows
Mingxuan Yi, Song Liu
Variational inference is a technique that approximates a target distribution by optimizing within the parameter space of variational families. On the other hand, Wasserstein gradie…
stat.ML2023★ 2 cited
MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows
Mingxuan Yi, Zhanxing Zhu, Song Liu
The conventional understanding of adversarial training in generative adversarial networks (GANs) is that the discriminator is trained to estimate a divergence, and the generator le…