Conditional GANs(cGAN), intheirrudimentary form,sufferfromcriticaldrawbacks such as the lack of diversity in generated outputs and distortion between the latent and output manifolds.

Imagine trying to track one particular fruitfly in a swarm of hundreds. Higher biological visual systems have evolved to track moving objects by relying on boththeirappearance andtheirmotiontrajectories.

Thefaithfulnessassumption allows us to infer dependence relations based on d-separation:Pis said to be faithful to graphD when the following holds: Any three variablesX,Y,Z that are not d-separated are conditionally dependent,i.e.,X 6 Y |Z inP.

Second, common entropy can be used to improve constraint-based methods such as PC or FCI algorithms in the small-sample regime,wherethesemethods areknowntostruggle.