the development of new consistency regularization or entropy minimization approaches,
often resulting in models with complex training strategies to obtain the desired results. In this
work, we instead propose a novel approach that explicitly incorporates the underlying
clustering assumption in SSL through extending a recently proposed differentiable
clustering module. Leveraging annotated data to guide the cluster centroids results in a …