NeurIPS 2020

Disentangling by Subspace Diffusion

Meta Review

The paper reduces the question of whether unsupervised disentangling is possible to the question of whether unsupervised metric learning is possible, providing a unifying insight into the geometric nature of representation learning. All reviewers think the theory and algorithm developed for decomposing Lie group is novel. The paper is missing citations of previous work related to fibre bundle, and manifold learning, which the authors should remedy in the revised version.