Alex Wiltschko

Composing graphical models with neural networks for structured representations and fast inference

We propose a general modeling and inference framework that combines the complementary strengths of probabilistic graphical models and deep learning methods. Our model family composes latent graphical models with neural network observation likelihoods. For inference, we use recognition networks to pr…