Then we introduce a semantic mapper that produces the proxy masks from various input conditions including semantic masks.

The UN estimates 2-5% of global GDP or $0.8 - $2.0 trillion dollars are laundered

We further introduce a multi-scale diversity penalty that operates in the feature space of our discriminators.

In variational inference, the benefits of Bayesian models rely on accurately capturing the true posterior distribution. We propose using neural samplers that specify implicit distributions, which are well-suited for approximating complex multimodal and correlated posteriors in high-dimensional spaces.

Lemma 3. Consider the ReLU activation The proof of Theorem 1 is given below. The inequality 3 uses strictly monotone property of p () . Code is available at this link. The neural networks are updated using Adam with learning rate initializes at 0.035 and All of them have no communication constraints. The training time is shown in Table 1.