Bounding the Test Log-Likelihood of Generative Models

Several interesting generative learning algorithms involve a complex probability distribution over many random variables, involving intractable normalization constants or latent variable marginalization. Some of them may not have even an analytic expression for the unnormalized probability function and no tractable approximation. This makes it difficult to… CONTINUE READING