To this end, we adopt prototypical networks (Snell et al., 2017), a metric learning approach, to solely rely on the encoders to form the classifiers instead of introducing additional classification layers.
multi-view spectral clustering can work with representations that are separately learned for the individual views and the multi-view information is aggregated using the common eigenvectors of the data similarity Laplacian matrices.