We propose a new perspective to reconsider theFourier transform from abasis functions perspective. Specifically, the real and imaginary parts of the frequency components can be viewed as the coefficients of cosine and sine basis functions at tiered frequency levels, respectively.

For e.g., they assume pre-specified

In this paper, we study the generalization properties of Model-Agnostic MetaLearning (MAML) algorithms for supervised learning problems.

V anilla NA T model assumes that the target tokens are independent of each other given the source sentence. This assumption enables the parallel generation of all tokens.

Notsurprisingly, GVS also inherits the challenges of both: generating RGB values from a bare semantic map is an ill-posed problem that is further complicated by the need for the different output views to be photometrically and geometrically consistent. One could tackle this problem with the sequential application ofexisting techniques.