Machine Learning, Deep Learning, Generative Model, Adversarial Network, Autoencoder.
can decode. Gradients can’t flow through random nodes. We use reparameterization trick (see fig) to make the network differentiable. We sample from N(μ(X), Σ(X)) by first sampling ε ∼ N(0, I), then computing z=μ(X) + Σ1/2(X)∗ε. This has been very beautifully shown in the figure 2[1]? . It should be