We propose a new class of generative models that naturally handle data o...
Recent progress with conditional image diffusion models has been stunnin...
We introduce a framework for automatically defining and learning deep
ge...
We present a framework for video modeling based on denoising diffusion
p...
We consider image completion from the perspective of amortized inference...
We propose a method for improved training of generative adversarial netw...
In this work we demonstrate how existing software tools can be used to
a...
We present a new approach to automatic amortized inference in universal
...
We introduce the use of Bayesian optimal experimental design techniques ...