Documentation for Burger equation discovery #3
Description
I ran python3 ./main.py with setting.txt set to Discovery and then to Extraction.
But the output seems strange:
The #1 most likely PDE gives a residual of 0.0071 (3953.11% better than the next sparsest PDE).
D_t U = -1.986161 + -0.159162(U) + -0.120095(D_x U) + -0.473282(D_x^2 U) + -0.111699(U)(U) + -0.825335(U)(D_x^2 U) + -0.020040(U)(U)(U) + -0.253458(U)(U)(D_x^2 U)
Do you need some special set of hyperparameters to recover the Burger equation appropriately?
On this note, it would benefit both the paper and the repo to have a kind of jupyter notebook tutorial rather than putting everything in README or settings.