ifm

In this section we give proofs for all the results in Sec. 2, which explores the phenomenon of feature We invite the reader to consult Sec. For this purpose we found this strong notion of distinguishing to suffice. The encoder must learn color features in order to identify this positive pair. Proposition 2. F or a set S [ n ] of features let L By Prop 2.3, we know that for each This section gives detailed derivations of two simple but key facts used in the development of IFM. The first result derives an analytic expression for the gradient of the InfoNCE loss with respect to positive sample in latent space, and the second result computes the gradient with respect to an arbitrary negative sample.