Deep Generative Learning via Variational Gradient Flow

24 Jan 2019Yuan GaoYuling JiaoYang WangYao WangCan YangShunkang Zhang

We propose a general framework to learn deep generative models via \textbf{V}ariational \textbf{Gr}adient Fl\textbf{ow} (VGrow) on probability spaces. The evolving distribution that asymptotically converges to the target distribution is governed by a vector field, which is the negative gradient of the first variation of the $f$-divergence between them... (read more)

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