Review for NeurIPS paper: Learning Disentangled Representations and Group Structure of Dynamical Environments

While the rebuttal did address some of my concerns, I can not raise further. Especially, since I would still like to see an experiment analysis added on a standard benchmark where the proposed method **fails** (perhaps this is the case for the promised experiments on 3D cars or 3D shapes, but this is not clear from the text). In this way, it should be easier for others to follow-up on this work. I also recognize the scalability issues of the proposed method as pointed out by R2 and R5, which I initially had not considered. I agree that this is an issue that should be discussed in the paper and ideally computational complexity is empirically analyzed. However, considering that the field of disentanglement is still rather nascent and mostly concerned with synthetic datasets and overengineered methods, I don't think this is reason for rejection or a lower score.