As compared to TFN which uses a single outer product to obtain a multimodal tensor of rank one, T2FN creates a tensor of high rank (upper bounded by T ).
the notion of rank naturally emerges when we reason about the properties of M. We first state several observations about the rank of multimodal representation M: 1) r noisy : The rank of M is maximized when data entries are sampled from i.i.d.