Reviews: Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis

I appreciated the author's responses, and I think the proposed refinements will strengthen the manuscript. As such, I decided to increase my score: 5 - 6. However, I remain lukewarm regarding the actual results shown in the paper. I found the comparisons to be limited (the authors still resist performance comparisons with common approaches such as GPFA or LDS in Figure 1), and the performance quantifications to not be very elucidating (they are focused solely on modest gains in predictive performance whereas the strongest motivation for this method is interpretability). Given that what I find most exciting in this submission is the potential for interpretability, I'm pretty disappointed no effort is done to explore this avenue in the results. To be clear, I agree that it is unreasonable to expect fully featured scientific results in a NeurIPS submission, but I would have liked to at least see this interpretability aspect briefly explored.