def __call__(self):
W = self.W()
cov = W @ tf.transpose(W) + self.sigma() * tf.eye(W.shape[0])
return pf.MultivariateNormal(tf.zeros(W.shape[0]), cov)
def __call__(self):
cov = tf.eye(2) + self.rho() * tf.abs(tf.eye(2) - 1)
return pf.MultivariateNormal(tf.zeros([2]), cov)