Supplementaryto" Instance-dependentLabel-noise LearningunderaStructuralCausalModel "

Let S be the noisy training set, andd2 be the dimension of an instancex. Let y1 and z1 be the estimated clean label and latent representation for the instancex, respectively, by the first branch. As mentioned in our main paper (see Section 3.2), the negative ELBO loss is to minimize 1). a reconstruction lossbetween eachinstancexand ˆpθ11(x,y1);2). For co-teaching loss, we directly follow Han et al. [1].