These papers focus on building the symmetries into the models by modifying the architecture.

The pursuit of realistic image synthesis at arbitrary views, given only a single source image, has long been a cornerstone challenge in computer vision and graphics.

Federated Learning (PFL) has emerged, where personalized models are trained for individual clients.

The probabilities that a user likes each item are unknown.