We propose the Interferometric Graph Transform(IGT), which is a new class of deep unsupervised graph convolutional neural network for building invariant graph representations. Our first contribution is to propose a generic, complex-valued spectral graph architecture obtained from a generalization of the Euclidean Fourier transform. We show that our learned representation consists in both discriminative and invariant features, thanks to a novel greedy concave objective. From our experiments, we c…