NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID: 5810 Superposition of many models into one

### Reviewer 1

I have a few comments which I hope Authors can address to make this paper stronger and more complete: 1- Related work is minimal. Although there is a short paragraph compare your results with previous work, but it is not enough. The reader should get more insight about previous approaches and a high-level understanding of why previous approaches are different than yours. Please expand this section. 2- There are some confusions and inconsistencies in experimental results, section 4.1.3, paragraph "choosing context parameters": 2.1- I see in Figure 5-right that you present results for pspLocalMix, but I couldn't find what approach it refers to. 2.2- The text says: "... Figure 5 right shows that while pspFast is better than standard model ..." but standard model results are not in Figure5-right. It is a combination of Figure 4-b and Figure 5, right? 2.3- Does anywhere in the text talks about Figure5-left? 3- I think how many models can be stored in superposition with each other is a very interesting question and shouldn't be left out in this paper. I know Authors mentioned this in Future work and Discussion, but this is a fundamental question that directly related to the effectiveness of their proposed solution and at least some preliminary empirical results are required to be included in this paper. I understand Authors have realized degradation in performance while keeping 1000 models superposition-ed with each other, but it is very interesting to get more insight about the limitation of their approach in terms of the number of models stored together.