Weakness 1. It is hard to understand what the axes are for Figure 1. 2. It is unclear what the major contributions of the paper are. Analyzing previous work does not constitute as a contribution. 3. It is unclear how the proposed method enables better results. For instance, Table 1 reports similar accuracies for this work compared to the previous ones. 4. The authors talk about advantages over the previous work in terms of efficiency however the paper does not report any metric that shows it is more efficient to train with this proposed method. 5. Does the proposed method converge faster compared to previous algorithms? 6. How does the proposed methods compare against surrogate gradient techniques? 7. The paper does not discuss how the datasets are converted to spike domain.
There are no potential negative societal impacts. One major limitation of this work is applicability to neuromorphic hardware and how will the work shown on GPU translate to neuromorphic cores.
5. Does the proposed method converge faster compared to previous algorithms?