ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA

We consider the identifiability theory of probabilistic models and establish sufficient conditions under which the representations learned by a very broad family of conditional energy-based models are unique in function space, up to a simple transformation. In our model family, the energy function is the dot-product between two feature ex...More