Reviews: STAR-Caps: Capsule Networks with Straight-Through Attentive Routing

The presented routing mechanism differs from routing by agreement in that routing coefficients are not iteratively determined by evaluating agreement of votes, but by computing self-attention scores and binary routing decisions for each combination of input and output capsules. The combined routing procedure seems to be novel, while the individual parts are inspired by self-attention in the transformer and Gumbel-softmax decisions as used in discrete domains like text processing. The paper is technically sound and is very well written, precisely explaining the method and architecture. I feel confident that I could reproduce the method given the provided information. The paper achieves its goal in providing a more efficient substitute for routing by agreement, which allows the architecture to be applied on real-world datasets like ImageNet, as is shown by the experiments.