The lottery ticket hypothesis suggests that sparse, sub-networks of a given neural network, if
initialized properly, can be trained to reach comparable or even better performance to that of
the original network. Prior works in lottery tickets have primarily focused on the supervised
learning setup, with several papers proposing effective ways of finding winning tickets in
classification problems. In this paper, we confirm the existence of winning tickets in deep
generative models such as GANs and VAEs. We show that the popular iterative magnitude …

The lottery ticket hypothesis suggests that sparse, sub-networks of a given neural network, if
initialized properly, can be trained to reach comparable or even better performance to that of
the original network. Prior works in lottery tickets have primarily focused on the supervised
learning setup, with several papers proposing effective ways of finding" winning tickets" in
classification problems. In this paper, we confirm the existence of winning tickets in deep
generative models such as GANs and VAEs. We show that the popular iterative magnitude …