Review for NeurIPS paper: Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks

Additional Feedback: I read the author feedback. It answers my question well and was consistent with what I assumed in the original review. Therefore, I remain my positive evaluation. In my understanding, in standard multi-scale GNN, there are nonlinear activation in-between aggregation functions G. In this paper, there is no nonlinear activation in-between aggregation functions G. Nonlinear activation is only in B. Therefore, "graph" part G is always linear. Is there such multi-scale GNN in the literature?