Hi everyone,
in the reparametrize function of the vae example 72, line 54 on github
    def reparameterize(self, mu, logvar):
        std = torch.exp(0.5*logvar)
        eps = torch.randn_like(std)
        return eps.mul(std).add_(mu)

What is the theoretical reason to multiply the log variance vector with 0.5? What if you change it to 1 or 0.1?
Thanks niclas