Before revision:  The resulting WSINDy _PDE algorithm uses separable test functions implemented efficiently via convolutions for discovery of PDE models with computational complexity O(NM)from data points with M = N ^{D+1(N^{D+1}\log(N)) for datasets with N points } in each of D+1 dimensions .
After revision:  The resulting WSINDy algorithm for PDEs has a worst-case computational complexity of \mathcal{O(N^{D+1}\log(N)) for datasets with N points } in each of D+1 dimensions .